This repository contains data mining assignments that were given in the fall 2021 semester.
For each assignment, a report outlining algorithms and code is supplied (In Farsi).
Algorithms implemented in each assignment are:
- Assignment 1:
- Linear regression using gradient descent and stochastic gradient descent (from scratch).
- Data preprocessing using pandas
- Assignment 2:
- Data preprocessing
- Decision tree using gini and entropy as criterion (from scratch)
- K-nearest neighbor (from scratch)
- Naive bayes (from scratch)
- Assignment 3:
- Linear SVM (from scratch)
- Non-linear SVM
- Random Forest (from scratch)
- Adaboost
- Assignment 4:
- K-Means clustering (from scratch)
- PCA (from scratch)