"This repository contains implementations of Boosting method, aimed at improving predictive performance by combining multiple models. by using titanic database."
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Updated
Jun 30, 2024 - Jupyter Notebook
"This repository contains implementations of Boosting method, aimed at improving predictive performance by combining multiple models. by using titanic database."
"This repository contains implementations of Boosting method, popular techniques in Model Ensembles, aimed at improving predictive performance by combining multiple models. by using titanic database."
The project's objective is to harness a HR Analytics dataset. With predictive proccess I tried to equip HR management with actionable insights, enabling them to proactively address attrition issues and implement targeted retention strategies.
This is a data mining project that analyzes apple quality attributes to classify apples as "good" or "bad." We use Exploratory Data Analysis (EDA) to visualize data distributions and identify key factors. The study offers recommendations for improving apple production and marketing.
Web Based application with various operations for data science
A project for streaming algorithms: Bloom filtering, Flajolet-Martin Algorithm, Fixed-Size Sampling
Data Mining Model For Detection of Fraudulent Behaviour
Market basket analysis is a technique used mostly by retailers to identify which products clients purchase together most frequently. This involves analyzing point of sale (POS) transaction data to identify the correlations between different items according to their co-occurrence in the data.
Data Mining for Research Diary at Indiana University
Data minnig GUI project to predict laptop prices,I uses most of ML algorithmes here
Practice codes for Machine Learning, Data Mining and NLP in Python
Experimenting with clustering, classification and association analysis with various csv files.
Datamining concepts
In this project, data mining and time series analysis algorithms are used to predict whether people are present in a room based on physical information such as CO2 or humidity levels in the air.
In this project we tried to solve a $10000 Kaggle competition. Starting with a dataset containing information about buying and selling used cars, we want to determine whether a purchase is a good or a bad purchase through the use of state-of-the-art Machine Learning and AI algorithms.
Course Project of Information Retrieval.
This contains all projects that I have done during my master degree.
FP Growth algorithm implemented using python
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