This report is regarding to the project for Statistical Learning Course in Shahid Beheshti University, Faculty of Mathematics and Computer Science. This report covers the following contents:

To learn about the data set please follow these links.

• Dataset Description
• Dataset Web site

Dataset for clustering is:

• Clustering Dataset Web site

To view result please follow these links:

• Regression Results (project #1)
• Classification Results (project #2)
• SVM Results (project #3)
• Clustering Results (project #4)
• Neural Network Results (project #5)

This project is developed on Python. In order it you will need the following python-packages installed. You can download and install them via pip tool.

• numpy
• sklearn
• scipy
• metrics
• pandas
• keras (for running NN)
• tensorflow (for running NN)

In order to run the project, inside the project root folder call the run.py with a project name argument. By running each project it will run and illustrate its results.

python run.py PROJECT_NAME

Where PROJECT_NAME could be one of these:

• classification or cl for running Classification
• bench-mark or bm for running Bench-Mark
• feature-selection or fs for running Feature Selection on regression data
• linear-regression or lr for running Linear Regression
• reg-all for running all Regression based modules
• kmeans or km for running k-means clustering
• hierarchical-clustering or hc for running Hierarchical Clustering (Agglomerative-Clustering)
• neural-networks or nn for running Neural Network Classification

You can also run these commands for running projects based on the part they’re described in:

• p1 for running part #1 (Regression)
• p2 for running part #2 (Classification)
• p3 for running part #3 (SVM)
• p4 for running part #4 (Clustering)
• p5 for running part #5 (Neural Network)

In order to read more about this project please follow this link: https://github.com/ArefMq/ML-Project/blob/master/report.pdf