Write a code to implement AdaBoost algorithm using decision stump to learn strong classifier

Implementation of decision trees for binary categorical data using numpy. Includes regular decision trees, random forest, and boosted trees.

Face Detection by AdaBoost learning. Conformal Geometric Algebra is applied for feature extraction.

A classification project to determine the eligibility of getting a loan after filling an online form

CART, K-Means, Apriori, Adaboost, RFE; models using Anti-cancer peptides vs Human proteins

Use patient health data from MIT's GOSSIS(Global Open Source Severity of Illness Score) to do an experiment, in which we want to evaluate the question of which modeling strategy leads to the most effective predictions.

Machine Learning models compared to find the strongest predictor for credit risk

This is my college practice work, where i try to learn and cover all the tree based regression algorithms (preferably in python).

Bill Gates was once quoted as saying, "You take away our top 20 employees and we [Microsoft] become a mediocre company". This statement by Bill Gates took our attention to one of the major problems of employee attrition at workplaces. Employee attrition (turnover) causes a significant cost to any organization which may later on effect its overal…

Predict whether income exceeds 50K/yr based on census data.

Boosted multi-task learning for face verification

Language detector - Classification Algorithm

Implementation of various machine learning algorithms from scratch.

CharityML is a fictitious charity organization located in the heart of Silicon Valley that was established to provide financial support for people eager to learn machine learning. After nearly 32,000 letters were sent to people in the community, CharityML determined that every donation they received came from someone that was making more than $5…

In this project, we analyze and compare the performance of various machine learning algorithms (Linear Regression, Decision Tree, AdaBoost, XGBoost, Gradient Boosting and k- Nearest Neighbors) when used to predict hard drive failures using Backblaze data in the year 2018.

First project Of machine learning Nanodegree (Supervised Learning)

A classification project to determine if a passenger survived the Titanic crash or not.

Adaboost, short for Adaptive Boosting, is a popular and powerful ensemble learning algorithm used in machine learning.