Lime Classification Python

If the feature is numerical, we compute the mean and std, and discretize it into quartiles. LIME, which is available in a Python implementation on github, goes further than this by “perturbing” sample input (as its authors put it in another article, “by changing components that make sense to humans (e. What we'll do instead is run LIME on a representative sample of test cases and see. Matt Harrison here, Python and data science corporate trainer at MetaSnake and author of the new course Applied Classification with XGBoost. The best split is. stateful_lstm: Demonstrates how to use stateful RNNs to model long sequences efficiently. This probability is then converted to a prediction of either leave or stay through a process called Binary. 7 syntax which does not always work in 3. They kill their prey by constricting it, using their strong muscles and coiled bodies to suffocate their prey. EQ2Wire is proud to offer a website built on the EQ2 Data Feeds API. , a deep learning model that can recognize if Santa Claus is in an image or not):. the flying fox; the python, the cobra, and many other varieties of snake, including the hamadryad; the alligator, the otter and the gavial, as well as countless kinds of squirrel, rat, &c. From our experiments, the results were strikingly close to what a human would draw around the leopard. Stomach-churning moment a python regurgitates a LIVE 4ft monitor lizard and the reptile scampers off. In a normal decision tree, one decision tree is built and in a random forest algorithm number of decision trees are built during the process. Plan your Islamorada Florida Keys vacation with Fla-Keys. Newspaper is easy to clean, but it's not aesthetically pleasing for some people. me converts your code snippets into pretty-printed HTML format, easily embeddable into blog posts, emails and websites. Search for ticker symbols for Stocks, Mutual Funds, ETFs, Indices and Futures on Yahoo! Finance. Written by Keras creator and Google AI researcher … Continue reading →. imports the package ragged2e and left-justifies the text. Miller DuraFlex Stretchable Harnesses Patented Miller DuraFlex Harnesses feature specially-formulated elastomer webbing that stretches. Navigation of files and paths in your drive for any file. He wears a white T-shirt with a blue collar and blue sleeves, though his sleeves hang loose, given that he has no arms. Let's jump into implementation for the same to check the local interpretation of a given prediction using LIME:. A famous example are deep neural nets, in text classification oftern recurrent or convolutional neural nets. Information on surveys, certification, examination, testing and contact details. These IS codes include the Standardization in the field of all types of cement, pozzolana, testing sand, concrete, aggregates, instruments for cement and concrete testing, cement plant machinery and ferrocement concrete, reinforced concrete and pre-stressed concrete, test methods for concrete. Miscellaneous. Package authors use PyPI to distribute their software. Intuitive, open, and continuously integrating new developments, KNIME makes understanding data and designing data science workflows and reusable components accessible to everyone. Along with the high-level discussion, we offer a collection of hands-on tutorials and tools that can help with building your own models. I've framed this project as a Not Santa detector to give you a practical implementation (and have some fun along the way). Nicholas is a professional software engineer with a passion for quality craftsmanship. Learn more. Every machine. SciPy 2D sparse array. Python in Data Science is huge right now. In the previous tutorial, we looked at lime in the two class case. Sat Aug 10 2019 at 10:00 am, This is a special experience. You'll love the slick user interface, extraordinary features and amazing performance. Hey everyone. Method overriding in C# is a feature like the virtual function in C++. 05″ step ribbon CABLE-40-40-10CM and allow LIME GPIOs to be used with BREADBOARD-1, or with A13-LCD43TS, A13-LCD7TS or A13-LCD10TS. These algorithms give meaning to data that are not labelled and help find structure in chaos. The following are code examples for showing how to use matplotlib. Random forest uses the classification results voted from many. See Probabilistic Programming in Python using PyMC for a description. Download Open Datasets on 1000s of Projects + Share Projects on One Platform. The class can be used directly, or by calling shelve. Random forest is capable of regression and classification. In the case of a linear kernel, n_classes * (n_classes - 1) / 2 individual linear binary models are fitted for each possible class pair. And the balloon classification was based on the association with the shape of the 'heart' with balloons. Corey Maynard said on May 19, 2013: @Sauld - There's some hints to how I did that in there. 10 Best Python IDEs. Local Interpretable Model-agnostic Explanations (LIME) Instead of training an interpretable model to approximate a black box model, LIME focuses on training local explainable models to explain individual predictions. Learn how to package your Python code for PyPI. This is a Development Build. See the complete profile on LinkedIn and discover Kenechukwu’s connections and jobs at similar companies. For classification where the machine learning model outputs probabilities, the partial dependence plot displays the probability for a certain class given different values for feature(s) in S. We take the image on the left and divide it into interpretable components (contiguous superpixels). And with the new(ish) release from March of package by Thomas Lin Pedersen's, lime is now not only on CRAN but it natively supports Keras and image classification models. NET has been designed as an extensible platform so that you can consume other popular ML frameworks (TensorFlow, ONNX, Infer. Paste the following code in a python file; Execute it (either selecting the code or using the Run cell code lens). Sources: Marco Tulio Ribeiro, Pixabay. In this article, we will go through step by step details of implementing data science lifecycle using Python. Best Training Institute for IT Software Hardware & Networking Courses in Noida provided by APTRON. Matches any character except. (none are for python, though, which is a dang shame :/) That being said, I am making progress! I’ve narrowed down what I need to do to finish off Wynn and Anna’s routes, and I’m going strong into the planning phases of the next one (Raul!). Sublime definition is - to cause to pass directly from the solid to the vapor state and condense back to solid form. —In this paper we will discuss pandas, a Python library of rich data structures and tools for working with structured data sets common to statistics, finance, social sciences, and many other fields. To apply LIME we just need a function to make predictions on texts. Children can be either element nodes or text (including whitespace). Dear SpigotMC Community, It is my pleasure to announce that development builds for the Minecraft 1. View Mark Van den Broek’s profile on LinkedIn, the world's largest professional community. The P columns are selected at random. Package authors use PyPI to distribute their software. Personality Edit. The workshop, led by Loren Collingwood, covered the basics of content analysis, supervised learning and text classification, introduction to R, and how to use RTextTools. We can implement the LIME technique in both R & Python using the LIME package. (4 replies) I'm new to python so appologies to the group if this question is asked often. Usually, the default choice of P is p/3 for regression tree and P is sqrt(p) for classification tree. Comments, processing instructions, and CSS content do not affect whether an element is considered empty. In contrast to the techniques described in the first article, LIME is even applicable to models for text and image classification. Neither of them applies LIME to image classification models, though. The green tree python (Morelia viridis), is a species of python native to New Guinea, islands in Indonesia, and Cape York Peninsula in Australia. Welcome to ELI5's documentation!¶ ELI5 is a Python library which allows to visualize and debug various Machine Learning models using unified API. I gave the Python implementation a shot. This book is a guide for practitioners to make machine learning decisions interpretable. Getting tired of cutting & pasting an HTML5 template? Or typing out the same code all the time? Fortunately, Sublime Text makes it easy to quickly insert code snippets that you define. More than 1 year has passed since last update. text_explanation_lime: How to use lime to explain text data. Hopefully most of you are now familiar with how these releases work, so I will try to be brief with the details, but please still make sure you read this post in its entirety. CODE OF CONDUCT. World Class Solitaire HD Play FREE online games ! Welcome to Pogo. 3 to commit 8e3b9bf917a7, and SQLite to 3. You train your classifier, and it yields 99. Explaining the Predictions of Any Classifier, which proposes the concept of Local Interpretable Model-agnostic Explanations (LIME). Machine Learning Training: You'll learn how to use H2O Automated Machine Learning for a binary classification problem. You'll learn. 1 character classification. See for more background: LIME paper. Vegetables are classified according to which part of the plant is eaten. The number at the beginning of that last class of ages, is also the number N last at the end of the previous class, that is, N final is the initial number of survivors of the class before last. After completing this tutorial you will know how to implement and develop LSTM networks for your own time series prediction problems and other more general sequence problems. The lime package also works with text data: for example, you may have a model that classifies a paragraph of text as a sentiment "negative", "neutral" or "positive". Along with the high-level discussion, we offer a collection of hands-on tutorials and tools that can help with building your own models. The third and fourth represents intensity of green and fifth and sixth represents the intensity of blue. From our experiments, the results were strikingly close to what a human would draw around the leopard. Frequent, year-round start dates for many courses and programs. Being able to go from idea to result with the least possible delay is key to doing good. Therefore I wanted to play around with the method a little bit. Nicolas Thiebaut's data science blog. The only downside might be that this Python implementation is not tuned for efficiency. It provides a high-level interface for drawing attractive and informative statistical graphics. K-LIME generates global and local explanations that increase the transparency of the Driverless AI model, and allow model behavior to be validated and debugged by analyzing the provided plots, and comparing global and local explanations to one-another, to known standards, to domain knowledge. 92+, it seems impossible to reimport deactivated responses tables into new response tables if the survey was modified. 7 , numpy , scikit-image I am working on detecting certain areas on an image using scikit-image. From the above, it looks like the Logistic Regression, Support Vector Machine and Linear Discrimination Analysis methods are providing the best results (based on the ‘mean’ values). Gurunath has 1 job listed on their profile. World Class Solitaire HD Play FREE online games ! Welcome to Pogo. Local Interpretable Model-Agnostic Explanations (LIME) is an attempt to make these complex models at least partly understandable. If you want to know the midpoint of the segment with endpoints (–4,–1) and (2,5), then plug the numbers into the midpoint formula, and you get. Modelling the tree in Python. predict_classes is used for generating class values as a matrix of binary ones and zeros. The workshop, led by Loren Collingwood, covered the basics of content analysis, supervised learning and text classification, introduction to R, and how to use RTextTools. More than 1 year has passed since last update. Nicholas is a professional software engineer with a passion for quality craftsmanship. LIME can be used to explain a number of different classifiers but I limited myself to image classification. It is intended to serve as a template for translation of the docstrings into different languages. 500+ Colours. See Probabilistic Programming in Python using PyMC for a description. Press J to jump to the feed. with 2 9120 Yellow/Lime Class Panels T-Shirt Stitch with Flat ML Kishigo 9120. Our programs make continuing education more accessible for the adult learner. Explaining the Predictions of Any Classifier, which proposes the concept of Local Interpretable Model-agnostic Explanations (LIME). Transforming an image into interpretable components. Use Yellowbrick in your work, referencing the Visualizers and API for assistance with specific visualizers and detailed information on optional parameters and customization options. Select code, right click and choose Run Selection/Line in python terminal. For example, lime (Pedersen and Benesty 2018) is a port of the LIME Python library (Lundberg 2019), while live (Staniak and Biecek 2018), localModel (Staniak et al. 4: The Kitten Picture Edition A new major release of lime has landed on CRAN. A python package was developed to support explaining individual prediction for text classification models or classifiers that built on numerical or categorical data or images. Local surrogate models are interpretable models that are used to explain individual predictions of black box machine learning models. The data collection component of research is common to all fields of study including physical. Simple language integrations use an existing REPL class (see below) without modification. I think you'll see why HornetOfJustice embodies #practicegoals - despite no formal education in art aside from "indifferent public school teachers" who may have done more harm than good, she has found a growth mindset that's allowed her to train herself, largely through online resources like Line of Action. But not all clustering algorithms are created equal; each has its own pros and cons. This facilitates collaboration across your organization, because users can program in the language of their choice. Written by Monty Python, directed by Terry Gilliam and Terry Jones. This kind of setup is possible if the majority of instances go left, only some right. It's almost as if she can sniff out the guilt on anyone hiding something. the classification with the highest numbers. Deep learning models have shown amazing performance in a lot of fields such as autonomous driving, manufacturing, and medicine, to name a few. LIME, an algorithm that can explain the predictions of any classi er or regressor in a faithful way, by approximating it locally with an interpretable model. A10-OLinuXino-LIME-UEXT is adapter board with Male connector on 0. Machine learning has great potential for improving products, processes and research. INTRODUCTION This is a short introduction to the art of programming, with examples written in the programming language Python. MSC Industrial Supply is the source for your metalworking and MRO needs. scikit_learn. Employee attrition (churn) is a major cost to an organization. Transforming an image into interpretable components. Modelling the tree in Python. The class attribute specifies one or more classnames for an element. It was developed with a focus on enabling fast experimentation. There’s a lot to learn about a colorless, odorless and tasteless spirit. For example, lime (Pedersen and Benesty 2018) is a port of the LIME Python library (Lundberg 2019), while live (Staniak and Biecek 2018), localModel (Staniak et al. Welcome to yellowbrick's documentation!¶ Yellowbrick is a suite of visual analysis and diagnostic tools to facilitate feature selection, model selection, and parameter tuning for machine learning. Join LinkedIn Summary. Choose from over 800 seasonal plants grown on our nurseries, delivered to your door in QLD NSW VIC SA ACT. He loves architecting and writing top-notch code. Yesterday it was the Church of Cyprus and today its the Church of Scotland that hacker @security_511 has breached and leaked data from. Bohan has 8 jobs listed on their profile. See the complete profile on LinkedIn and discover Bohan’s connections and jobs at similar companies. Discover Lime Green leggings at Zazzle! Use your own images and text or choose from thousands of patterns and designs. com, adding a leading data science platform to the Oracle Cloud, enabling customers to fully utilize machine learning. LIME, an algorithm that can explain the predictions of any classi er or regressor in a faithful way, by approximating it locally with an interpretable model. Choose the model you want to develop some trust with. Package authors use PyPI to distribute their software. Trains and evaluatea a simple MLP on the Reuters newswire topic classification task. At the moment, we support explaining individual predictions for text classifiers or classifiers that act on tables (numpy arrays of numerical or categorical data) or images, with a package called lime (short for local interpretable model-agnostic explanations). In this post you will discover how to develop and evaluate neural network models using Keras for a regression problem. how many people are there a) 30 b) 33 c) 36 d) none of these. On May 16, 2018, Oracle announced that it signed an agreement to acquire DataScience. Quadrilaterals: Classification A quadrilateral is a polygon with four sides. If you are doing "az login" using a service principal for automation, we recommend using azureml. For a brief introduction to the ideas behind the library, you can read the introductory notes. There are many special types of quadrilateral. Although there are over 1,000 different types of ball python morphs, we only list 26 of the more widely known ones. We take the image on the left and divide it into interpretable components (contiguous superpixels). In COSMIC we have standard classification system for tissue types and sub types because they vary a lot between different papers. Coupon Purchase Prediction Machine Learning Project. Quick Arcade Library Introduction Video. First let's understand how LIME works. A new major release of lime has landed on CRAN. But computers usually do not explain their predictions which is a barrier to the adoption of machine learning. Creating a simple REST API in PHP I’m the author of php-crud-api and I want to share the core of the application with you. JenkinsAPI and Python-Jenkins are object-oriented python wrappers for the Python REST API which aims to provide a more conventionally pythonic way of controlling a Jenkins server. Eastbay empowers athletes by offering the best selection of pro-grade gear available, along with the knowledge and advice needed to win on and off the field. Python in Data Science is huge right now. The below plot uses the first two features. SciPy 2D sparse array. This kind of setup is possible if the majority of instances go left, only some right. EQ2Wire is proud to offer a website built on the EQ2 Data Feeds API. In mathematics and computer science, an algorithm (/ ˈ æ l ɡ ə r ɪ ð əm / ) is a sequence of instructions, typically to solve a class of problems or perform a computation. See the complete profile on LinkedIn and discover Gurunath’s connections and jobs at similar companies. The functions return a rectangle representing the bounding area of changed pixels. It has built-in support for several ML frameworks and provides a way to explain black-box models. But not all clustering algorithms are created equal; each has its own pros and cons. TextExplainer allows to explain predictions of any text classifier using LIME algorithm (Ribeiro et al. It is not on CRAN (yet, I assume), but you can install it via Github:. Pythons are classified in the phylum Chordata, subphylum Vertebrata, class Reptilia, order Squamata, family Boidae. My Python is an earlier model in the cardboard wood grain box but with a lime green label designating Custom Shop work. See the complete profile on LinkedIn and discover Bharat Ram’s connections and jobs at similar companies. The application may add to this set if desired by using AddColour and may use it to look up colours by names using Find or find the names for the standard colour using FindName. It also allows the refinement of models (frog image) by biasing the model to focus on the 'face'. Learn all about coding, compare and select training, take free tutorials and learn a ton more. The Python Package Index (PyPI) is a repository of software for the Python programming language. Read this article in order to learn how to use an AutoML H2O model to predict attrition and how to use Lime to explain the predicted class. We can extend this formulation to allow for the model to make use of the pass values of the input and the output. 01483 561362. Lime supports explanations for individual predictions from a wide range of classifiers, and support for scikit-learn is built in. Install it with pip as usual, pip install lime. hidden) states. Navigation of files and paths in your drive for any file. At each node, it works as follows: - Fit a parent model to the node - Split the node into two child nodes, fit separate child models. In this article,. I found a relevant method at the following link: Comparison of Random Forest and Parametric Imputation Models for Imputing Missing Data Using MICE: A CALIBER Study | American Journal of Epidemiology | Oxford Academic A snippet is given below: Impu. Pandas builds on top of another important package, numpy. Below is an example of one such explanation for a text classification problem. Machine learning algorithms usually operate as black boxes and it is unclear how they derived a certain decision. This probability is then converted to a prediction of either leave or stay through a process called Binary. In the previous tutorial, we looked at lime in the two class case. View Kenechukwu Nnodu’s profile on LinkedIn, the world's largest professional community. A parallelogram is a quadrilateral in which both pairs of opposite sides are parallel. Therefore I wanted to play around with the method a little bit. If you've installed Apache Ant as described in the Installing Ant section, running Ant from the command-line is simple: just type ant. This forum can be viewed by all, but access to contribute must be requested. 06/21/2019; 17 minutes to read +9; In this article. Alphabetical color listing. After obtaining accuracy metric from my keras binary classification model, I need know what the model made the predictions. The P columns are selected at random. In order to answer, Willow first needs to figure out what movies you like, so you give her a bunch of movies and tell her whether you liked each one or not (i. National Institutes of Health (NIH), raking leaves or using other garden tools results in more than 76,000 injuries per year!. 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This sample notebook automates the task of creating groups in a Portal for ArcGIS or ArcGIS Online organization. Clustering algorithms are very important to unsupervised learning and are key elements of machine learning in general. Check out the Quick Start, try the Model Selection Tutorial, and check out the Oneliners. Plan your Islamorada Florida Keys vacation with Fla-Keys. The way I did it was using a unique token in the request. MIT OpenCourseWare makes the materials used in the teaching of almost all of MIT's subjects available on the Web, free of charge. Usually you would put an additional modeling block on top of Random Forest derived patch classification probabilities. In this introductory part, I will cover some basic concepts regarding AI explainability, the LIME algorithm, give a short introduction to the python LIME library, and discuss some possible modifications of it. (1) repr and str in python (1) Reverse string. Currently ELI5 allows to explain weights and predictions of scikit-learn linear classifiers and regressors, print decision trees as text or as SVG. LIME (local interpretable model-agnostic explanations) is a package for explaining the predictions made by machine learning algorithms. Become a Member Donate to the PSF. LimeImageExplainer (kernel_width=0. Hidden Markov Model (HMM) is a statistical Markov model in which the system being modeled is assumed to be a Markov process with unobserved (i. variational_autoencoder_deconv. Scratch is a free programming language and online community where you can create your own interactive stories, games, and animations. You train your classifier, and it yields 99. Figure 7: LIME pixels tracking a leopard as it moves through the mountains. Regardless of the type of prediction task at hand; regression or classification. We will use the popular Jupyter and scikit-learn tools to create models, train them, evaluate them, and finally interpret the results. Machine Learning Training: You'll learn how to use H2O Automated Machine Learning for a binary classification problem. This blog post is part two in our three-part series of building a Not Santa deep learning classifier (i. At the moment, we support explaining individual predictions for text classifiers or classifiers that act on tables (numpy arrays of numerical or categorical data) or images, with a package called lime (short for local interpretable model-agnostic explanations). - Patented DuraFlex stretchable webbing for greater comfort, safety and productivity - Quick-connect buckles on the chest and leg straps for easy donning - Breathable, comfort-touch ba. As a more complex plug in example, look at the attached python file: compile_current_file. We hope you find it useful. The FourWaySplitter widget is a custom widget, written in pure Python and is a part of the agw sub-library which can be found in wx. sublimate Synonym Discussion of sublime. LinearSVC — scikit-learn 0. Read this article in order to learn how to use an AutoML H2O model to predict attrition and how to use Lime to explain the predicted class. NetBeans IDE for PHP has support for continuous integration. I'm trying to explain the best action (maximum output) for each given input. See for more background: LIME paper. His first book, the first edition of Python Machine Learning By Example, was a #1 bestseller on Amazon India in 2017 and 2018. 05″ step ribbon CABLE-40-40-10CM and allow LIME GPIOs to be used with BREADBOARD-1, or with A13-LCD43TS, A13-LCD7TS or A13-LCD10TS. Official Site | Second Life - Virtual Worlds, Virtual Reality, VR, Avatars, Free 3D Chat. variational_autoencoder: Demonstrates how to build a variational autoencoder. LIME uses a pick-step to select a representative set of predictions or conclusions to explain. Permutationofeachtestcasetoexplain 2. The lime package also works with text data: for example, you may have a model that classifies a paragraph of text as a sentiment "negative", "neutral" or "positive". In this tutorial, we will use a subset of the Freddie Mac Single-Family Loan-Level dataset to build a classification model and use it to predict if a loan will become delinquent. In this article, you'll see top 30 Python libraries for Machine Learning. Model interpretability with Azure Machine Learning. Add your name or logo for 99¢. ) The data is stored in a DMatrix object. Included are sections on disease diagnosis and control and detailed information about turf diseases such as dollar spot, damping-off diseases, powdery mildew, and brown patch. I was wondering if 1) LIME can handle such models 2) is there a working example including categorical variables?. The following code runs with Python 2 and requires some adaptation to work with Python 3. The method that was introduced in the paper is called LIME (Local Interpretable Model-Agnostic Explanations) and comes with a python package. Text alignment can be manually controlled by several commands. Visualizing ML Models with LIME. From the above result, it's clear that the train and test split was proper. However I get explanations with all zero weights, as if LIME simply returns the initial values and does nothing. 10 Best Python IDEs. A new major release of lime has landed on CRAN. I'm only focusing on a single output. Package authors use PyPI to distribute their software. Note: all the code and additional files for this post can be downloaded from my OneDrive folder HERE. Using Python and Tableau to Scrape and Visualize Twitter User Data. Designed to be the industry's most adaptable enterprise LMS, eFront gives you complete control over your virtual training environment and your data. The green tree python (Morelia viridis), is a species of python native to New Guinea, islands in Indonesia, and Cape York Peninsula in Australia. It seems like both interpret the same DecisionTree in different ways. Timo has 9 jobs listed on their profile. Navigation of files and paths in your drive for any file. , words or parts of an image)”) to make it easier to identify which specific components of the input lead to a particular. LIME can be used to explain a number of different classifiers but I limited myself to image classification. The default color class used in W3. Today, Python is one of the most popular programming languages and it has replaced many languages in the industry. Lime is short for Local Interpretable Model-Agnostic Explanations. By the way, I was really amazed to know that Wes McKinney was able to develop pandas after only a few years of Python experience. This book is a guide for practitioners to make machine learning decisions interpretable. 06/21/2019; 17 minutes to read +9; In this article. We gathered a classification dataset using Bing on Spark. The standard deep learning tools for regression and classification do not capture model uncertainty. Machine Learning (ML) is coming into its own, with a growing recognition that ML can play a key role in a wide range of critical applications, such as data mining. For 40 years, Seagate has enabled exponential data growth with breakthrough hard drives, solid state drives, systems, and recovery services. [aeiou] Matches any single character included in the specified set of characters. The result is a static graph displayed in the Results window #%% import matplotlib. The main point here is that all examples below refer to binary classification predictions between driver pairs and the features used are the differences in the respective features of the drivers. This kind of setup is possible if the majority of instances go left, only some right. Building Trust in Machine Learning Models (using LIME in Python) Guest Blog , June 1, 2017 The value is not in software, the value is in data, and this is really important for every single company, that they understand what data they've got. And with the new(ish) release from March of package by Thomas Lin Pedersen's, lime is now not only on CRAN but it natively supports Keras and image classification models. Algorithms are unambiguous specifications for performing calculation , data processing , automated reasoning , and other tasks. Many snake keepers use various mulches or coconut-husk products because they are pleasing to the eye and also help provide the humidity to keep these animals healthy. See the complete profile on LinkedIn and discover Gurunath’s connections and jobs at similar companies. This course covers the basics to get started looking with classification and regression in Machine Learning. BTW, called Colt again to set up a date for return shipping. Two Headed Python in Zoos. 92+, it seems impossible to reimport deactivated responses tables into new response tables if the survey was modified. Image recognition goes much further, however. You can designate the text color on your web page using the 'color' attribute in the HTML font element. imports the package ragged2e and left-justifies the text. And with the new(ish) release from March of Thomas Lin Pedersen’s lime package, lime is now not only on CRAN but it natively supports Keras and image classification models.