CS 4375.501 | Machine Learning Models
LR-Direct
The Linear Regression script using the direct method, and hours as input and grades as response.
LR-Direct-Polynomial
The Linear Regression script using the direct method and a polynomial model.
LR-Direct-Many
The Linear Regression script using using the direct method and many feature-variables as input.
LR-SGD
The Linear Regression script using Stochastic Gradient Descent.
KMeans-Blobs
The K-Means method applied on 2D Blob-points.
KMeans-Moons
The K-Means method applied on 2D Moon-points.
Gaussian-3D
The plot of Gaussian densities: 3D and level sets.
Gaussian-Sampling
Sampling from a Gaussian density.
PCA-2D
Example of PCA on 2D points.
PCA-Reduction
Dimensionality reduction applied on 2D points, from 2D to 1D.
PCA-Noise
Sampling from a Gaussian density.
PCA-Handwriting
Example of dimensionality reduction on the dataset ’Handwriting’.
PCA-Eigenfaces
Showing eigenfaces via Python and PCA.
KNN-Iris
The K-Nearest Neighbor method applied on the Iris dataset.
KNN-Iris-K
The K-Nearest Neighbor method applied on the Iris dataset and using multiple values for K.
KNN-MNIST
The K-Nearest Neighbor method applied on the MNIST dataset.
Image-Handling
Load, handle and show images using OpenCV.
LogisticR-Simple
Logistic Regression method applied on the Social Networks Ads dataset.
LogisticR-Exploratory
Logistic Regression method applied on the Credit Card dataset.
DTree-Classification
Decision Tree method for classification of instances in a dataset.
DTree-Regression
Example of Decision Tree method for simple regression.