I was looking recently at the Python module toolz, a collection of convenience functions. A lot of these functions don’t…
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AUC-ROC Curve – The Star Performer! You’ve built your machine learning model – so what’s next? You need to evaluate…
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Confusion Matrix – Not So Confusing! Have you been in a situation where you expected your machine learning model to…
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The XGBoost algorithm is effective for a wide range of regression and classification predictive modeling problems. It is an efficient…
Continue ReadingROC Curves and Precision-Recall Curves for Imbalanced Classification
Most imbalanced classification problems involve two classes: a negative case with the majority of examples and a positive case with…
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(a comparison)Delving into the nature of random forest, walking through an example, and comparing it to logistic regression. Andrew HershyBlockedUnblockFollowFollowingJul…
Continue ReadingPredicting Cancer with Logistic Regression in Python
Predicting Cancer with Logistic Regression in PythonUnderstanding the data, logistic regression, testing data, confusion matrices, ROC curveAndrew HershyBlockedUnblockFollowFollowingJul 1SourceIntroduction:In my first logistic…
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For example, we would all be furious if our email program’s spam classifier was only able to detect 50% of…
Continue ReadingPositive or Negative? Spam or Not-spam? A simple Text classification problem using Python
First, we’ll learn what text classification really means. What is text classification?Text Classification(TC) is the process of assigning tags or…
Continue ReadingDetermining the Happiest Cities using Twitter Sentiment Analysis with BERT
In this article, we examine the state-of-the-art technology in Deep Learning today to determine the positivity of users tweets in…
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Continue ReadingPreventing Discriminatory Outcomes in Credit Models
Preventing Discriminatory Outcomes in Credit ModelsValeria CortezBlockedUnblockFollowFollowingJun 5Machine learning is being deployed to do large-scale decision making, which can strongly impact…
Continue ReadingMeasuring Performance: AUC (AUROC)
Measuring Performance: AUC (AUROC)Rachel Ballantyne DraelosBlockedUnblockFollowFollowingFeb 23The area under the receiver operating characteristic (AUROC) is a performance metric that you can…
Continue ReadingRecall, Precision, F1, ROC, AUC, and everything
Recall, Precision, F1, ROC, AUC, and everythingOfir Shalev (@ofirdi)BlockedUnblockFollowFollowingMay 27Your boss asked you to build a fraud detection classifier, so…
Continue ReadingAn Introduction to Evaluating Classification Models
Let’s look at the actual distribution of outcome. Target Class Distribution of Full Datasetsns. countplot(x=fraud['Class'])Here, the class imbalance, or the skewed…
Continue ReadingUsing Natural Language Processing To Rate The Sentiment of the Game of Thrones Finale
Using Natural Language Processing To Rate The Sentiment of the Game of Thrones FinaleUsing Vader and TextBlob to analyze the sentiment…
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In that case you catch every good investment but incur a significant cost. Also note that in the example ROC…
Continue ReadingChallenges in sentiment analysis: a case for word clouds (for now)
For example, if I only take the list of positive tweets and I get an aggregate sentiment score for the…
Continue ReadingOn Invariants.
On Invariants. What is an invariant?Andrew PritchardBlockedUnblockFollowFollowingMay 10The specification of a program should be its class invariantsAim to write programs…
Continue ReadingValidating Type I and II Errors in A/B Tests in R
Validating Type I and II Errors in A/B Tests in R#ODSC – Open Data ScienceBlockedUnblockFollowFollowingMay 10In the below work, we will…
Continue ReadingText Classification Every Engineer should be able to Build from Scratch — Naive Bayes
Or what is the relationship between each word and the review sentimental?NB is simply a systematic way of making predictions…
Continue ReadingHow to assess a binary Logistic Regressor with scikit-learn
How to assess a binary Logistic Regressor with scikit-learnBookmark this python function that makes assessing your binary classifier easy. Greg…
Continue ReadingHow to interpret a binary Logistic Regressor with scikit-learn
How to interpret a binary Logistic Regressor with scikit-learnGreg ConditBlockedUnblockFollowFollowingApr 17Functionality OverviewLogistic Regression is a valuable classifier for its interpretability.…
Continue ReadingSentiment Analysis: Beyond Words
First, I split each review into sentences, and used spaCy and gensim to get distinct topics that reviewers mentioned in…
Continue ReadingBinary Classifier Evaluation made easy with HandySpark
Binary Classifier Evaluation made easy with HandySparkDaniel GodoyBlockedUnblockFollowFollowingMar 11Photo by SJ Baren on UnsplashTLDR;HandySpark is a Python package designed to improve…
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