Art of Stat: Machine Learning

Supervised & Unsupervised Learning with Real Data

The Art of Stat: Machine Learning app includes methods for supervised and unsupervised learning, lets you split data into training and test sets, visualizes all methods, including predictions and heatmaps, and lets you assess the accuracy of your algorithm by showing the confusion matrix and more.

Included ML algorithms so far include:

• Multiple Linear Regression (including categorical predictors and interactions interactions)
• Multiple Logistic Regression (including categorical predictors and interactions interactions)
• Discriminant Analysis (Linear & Quadratic)
• Naive Bayes
• K-Means Clustering

Functionality:

• Provides various datasets (Palmer Penguins, Wine Quality, Heart Disease, Iris Flowers, Credit Card Defaults, ...) or lets user upload their own CSV file
• Split data into training and test sets
• Standardize Features
• Select continuous and/or categorical features (where appropriate)
• Visualize all methods (Scatterplots, Heatmaps), predicted labels or posterior probabilities
• Assess accuracy by displaying Confusion Matrix and accuracy statistics (including precision and recall) in multiple ways
• Make predictions for new observations

Modules in preparation:

• Decision Trees & Random Forests
• Nearest Neighbor