machine-learning-models 0.0.2

Implementations of most popular machine learning algorithms

About this repo

This repository contains my own implementations of the most popular machine learning models. It also has scripts for data preproccessing (datasets titanic and GaltonFamilies). For classification, I implemented my own class for nested cross validation. There are functions to evaluate model using confusion matrix (calculating accurancy, sensitivity, specificity, precision etc.) as well as to draw ROC curve.

Note

All of the models and validation were implemented by myslef, without using sklearn library. They were done for learning purposes. There is a seperate file named sklearn.py, in which I focused on exploring sklearn library

Models in this repo

1. Linear models

• Linear Regression
• Logistic Regression

2. Trees

• Regression Tree
• Decision Tree
• Random Forest

3. Boosting

• Adaboost
• Gradient boosting
• Extreme Gradient Boosting

4. SVM

• SVM primal bez jądra
• SVM dual z jądrem

5. Naive Bayes
6. K-nearest-neighbours

Python package

This repo can be installed as a package via command

pip install machine-learning-models

1. Using only models

# Adaboost
from machine_learning.src.Adaboost.AdaboostModel import Adaboost
# XGBoost
from machine_learning.src.ExtremeGradinetBoost.XGBoostModel import XGBoost
# Gboost
from machine_learning.src.GradientBoosting.GradientBoostingModel import GBoost
# KNN
from machine_learning.src.KNearestNeighbours.KNearestNeighboursModel import KNearestNeighbours
# Linear Regression
from machine_learning.src.LinearRegression.LinearRegressionModel import LinearRegressionModel
# Logistic Regression
from machine_learning.src.LogisticRegression.LogisticRegressionModel import LogisticRegression
# Naive Bayes
from machine_learning.src.NaiveBayes.NaiveBayesModel import NaiveBayes
# Random Forest
from machine_learning.src.RandomForest.RandomForestModel import RandomForest
# DEcision and Regression Tree
from machine_learning.src.RandomForest.Tree import DecisionTree
from machine_learning.src.RegressionTree.RegressionTreeModel import RegressionTree
# SVM
from machine_learning.src.SVM.SvmModel import SVM
from machine_learning.src.SVM.SvmModel import PrimalSVM

Author

Małgorzata Grzanka