Weighted and iterative KDE to improve outlier detection
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Updated
Aug 22, 2019 - Python
Weighted and iterative KDE to improve outlier detection
Leave-one-out Cross-validation for regression models
Wine Goodness Prediction
General methods for machine learning for digital biomarker discovery.
Repository containing my coursework in R showing my proficiency in a variety of machine learning algorithims.
What if we could leverage the many Disney intellectual properties and continue to earn revenue for an extended amount of time after the initial movie release?
This project aims to understand and implement all the cross validation techniques used in Machine Learning.
Data Mining project (Fall2023) involving the classification and clustering of Sars-Cov-2 gene expression RNA-seq data
Data is a Drag: Exploring Classical Machine Learning Algorithms on Small and Imbalanced Datasets
Using Linear and Quadratic discriminant analysis, KNN and Naive Bayes to develop a tool that can classify wines into one of the three types based on the other variables provided.
Prediction of Sales Prices of Houses
Built LDA and QDA models on variables obtained from Principal Component Analysis (PCA) and Kolmogorov-Smirnov (KS) and tuned by leave-one-out cross-validation (LOOCV) to predict fraudulent online advertising click traffic
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