W Brett KennedyinTowards Data ScienceA Simple Example Using PCA for Outlier DetectionImprove accuracy, speed, and memory usage by performing PCA transformation before outlier detection6d ago16d ago1
W Brett KennedyinTowards Data ScienceAn Introduction to Using PCA for Outlier DetectionA surprisingly effective means to identify outliers in numeric dataOct 22Oct 22
W Brett KennedyinTowards Data ScienceFormulaFeatures: A Tool to Generate Highly Predictive Features for Interpretable ModelsCreate more interpretable models by using concise, highly predictive features, automatically engineered based on arithmetic combinations of…Oct 62Oct 62
W Brett KennedyinTowards Data ScienceShared Nearest Neighbors: A More Robust Distance MetricA distance metric that can improve prediction, clustering, and outlier detection in datasets with many dimensions and with varying…Sep 198Sep 198
W Brett KennedyinTowards Data ScienceAchieve Better Classification Results with ClassificationThresholdTunerA python tool to tune and visualize the threshold choices for binary and multi-class classification problemsSep 73Sep 73
W Brett KennedyinTowards Data ScienceDistance Metric Learning for Outlier DetectionAn outlier detection method that determines a relevant distance metric between recordsAug 201Aug 201
W Brett KennedyinTowards Data ScienceCreate Stronger Decision Trees with bootstrapping and genetic algorithmsA technique to better allow decision trees to be used as interpretable modelsAug 91Aug 91
W Brett KennedyinTowards Data ScienceDoping: A Technique to Test Outlier DetectorsUsing well-crafted synthetic data to compare and evaluate outlier detectorsJul 9Jul 9
W Brett KennedyinTowards Data ScienceCounts Outlier Detector: Interpretable Outlier DetectionAn interpretable outlier detector based on multi-dimensional histograms.Jun 191Jun 191
W Brett KennedyinTowards Data SciencePRISM-Rules in PythonA simple python rules-induction systemJun 2Jun 2