SHAP-based validation for linear and tree-based models. Applied to binary, multiclass and regression problems.

• UpdatedApr 19, 2025
• Python

Feature selection package of the mlr3 ecosystem.

• UpdatedSep 11, 2025
• R

A Linear Regression model to predict the car prices for the U.S market to help a new entrant understand important pricing variables in the U.S automobile industry. A highly comprehensive analysis with detailed explanation of all steps; data cleaning, exploration, visualization, feature selection, model building, evaluation & MLR assumptions vali…

• UpdatedJul 28, 2020
• Jupyter Notebook

Engaged in research to help improve to boost text sentiment analysis using facial features from video using machine learning.

• UpdatedJan 12, 2018
• Jupyter Notebook

using Drebin dataset to distinguish between malwares and not malwares

• UpdatedJan 5, 2019
• Jupyter Notebook

HR Analytics Dataset

• UpdatedMar 29, 2019
• Python

This project showcases a Network Intrusion Detection System (NIDS) designed to bolster cybersecurity defenses against evolving threats

• UpdatedDec 10, 2024

Tumor prediction from microarray data using 10 machine learning classifiers. Feature extraction from microarray data using various feature extraction algorithms.

• UpdatedDec 21, 2020
• Python

Evaluating machine learning methods for detecting sleep arousal, bachelor thesis by Jacob Stachowicz and Anton Ivarsson (2019)

• UpdatedApr 12, 2020
• Python

The classification goal is to predict whether the client will subscribe (1/0) to a term deposit (variable y).

• UpdatedJan 20, 2020
• Jupyter Notebook

King County House Sales

• UpdatedAug 22, 2019
• R

A Jupyter Notebook with the analysis and prediction of Final Grades (Pass/Fail) for students of mechatronics engineering in several mechanic courses.

• UpdatedApr 18, 2024
• Jupyter Notebook

A Chinese automobile company Geely Auto aspires to enter the US market by setting up their manufacturing unit there and producing cars locally to give competition to their US and European counterparts. They have contracted an automobile consulting company to understand the factors on which the pricing of cars depends. Specifically, they want to …

• UpdatedApr 18, 2020
• Jupyter Notebook

Extended cross validation, feature selection methods for imbalanced data analysis

• UpdatedAug 11, 2018
• Jupyter Notebook

To model the demand for shared bikes with the available independent variables

• UpdatedApr 10, 2022
• Jupyter Notebook

Case Study for Churn Modelling in a NGO

• UpdatedOct 1, 2018
• Jupyter Notebook

Feature-Engg

• UpdatedNov 12, 2020
• Jupyter Notebook

Used CDC dataset for heart attack detection in patients. Balanced the dataset using SMOTE and Borderline SMOTE and used feature selection and machine learning to create different models and compared them based on metrics such as F-1 score, ROC AUC, MCC, and accuracy.

• UpdatedDec 16, 2022
• Python

Through this research, we are able to model a student’s final grade in a particular subject and link it directly to certain relevant features that influence the outcome. We use the C5.0 decision tree technique to model the data.

• UpdatedAug 13, 2019
• R

Developed a predictive real estate model leveraging XG Boost Regressor, integrating web-scraped market data with existing datasets to forecast daily store visits, achieving a MAPE of 13.3%, enabling strategic retail location decisions

• UpdatedMay 28, 2024
• Jupyter Notebook