Using classification trees to predict a hand written digit.

Creating a classification decision tree that predicts heart disease. 79% Recall and 70% Precision

This repo contains an R programming project that implements and compares decision tree models including C5.0, C5.4 and CART.

Performed segmentation analysis and predictive modeling on insurance broker performance to conclude a random forest model (highest AUC of 73%) predicted whether 2020 Gross Written Premium will increase or decrease from 2019 with a misclassification rate of 35%. Four classification models (classification trees, logistic regression, random forests…

Build, train and deploy ML model to classify penguin types on tabular data

Using Logistics, Classification, and KNN modelling to predict if a credit card account will default.

A collection of mini projects in R that apply statistical and machine learning methods and tools to solve data-driven problems

A set of tools useful for doing experiments with fuzzy forests

Using the tree library to construct a classification tree

Classification of movie rankings

Analyze the ATM dataset and predict the monthly withdrawal and rating of an ATM based on the features in the dataset 🏧

Finding out whether it is possible to predict the quality of the wine using Random Forests, Neural Networks, Classification trees and other methods

BigData, Classification, Clustering, Graph analytics, Splunk, Spark, Neo4j, KNIME

Classification on the Kobe Bryant Shot Selection dataset (https://www.kaggle.com/c/kobe-bryant-shot-selection/data) using Decision Trees

Focused customer retention programs

ML projects, which I worked on utilising different machine learning algorithms.

from Wesleyan University

We predicted whether there is less chance or more chance of heart disease by exploring different Data Mining techniques like logistic regression, classification trees, and neural networks. We employed various algorithms and choose the model which gives the best prediction results by comparing the accuracy measures to avoid overfitting.

Python & SQL Languages. Code Files & Written Report. A brief overview of the project's goals and outcomes is given below.