This repository contains an example of each of the Ensemble Learning methods: Stacking, Blending, and Voting. The examples for Stacking and Blending were made from scratch, the example for Voting was using the scikit-learn utility.

Pixel based classification of satellite imagery - feature generation using Orfeo Toolbox, feature selection using Learning Vector Quantization, CLassification using Decision Tree, Neural Networks, Random Forests, KNN and Naive Bayes Classifier

Use machine learning models to detect lies based solely on acoustic speech information

Udacity capstone project | Credit card fraud prediction | Supervised Learning | Ensemble model | Data Sampling

The purpose of this analysis was to create a supervised machine learning model that could accurately predict credit risk using python's sklearn library.

This contains the Jupyter Notebook and the Dataset for the mentioned Classification Predictive Modeling Project

Some example projects that was made using Tensorflow (mostly). This repository contains the projects that I've experimented-tried when I was new in Deep Learning.

Determining whether two questions are asking the same thing can be challenging, as word choice and sentence structure can vary significantly. Traditional natural language processing techniques been found to have limited success in separating related question from duplicate questions. In this paper, we explore methods of determining semantic equi…

In this project, the success results obtained from SVM, KNN and Decision Tree Classifier algorithms using the data we have created and the results obtained from the ensemble learning methods Random Forest Classifier, AdaBoost and Voting were compared.

Multiple Model Ensembling

This toolbox offers 8 machine learning methods including KNN, SVM, DA, DT, and etc., which are simpler and easy to implement.

Detection of Object-Based Forgery in Advanced Video

📄 Official implementation regarding the paper "Creating Classifier Ensembles through Meta-heuristic Algorithms for Aerial Scene Classification".

Spam Detection – Cluster SMS messages to “Spam” and “Ham” (Kaggle Challenge)

Predictive lead scoring for corporate loan data

How to Train an Ensemble of Convolutional Neural Networks for Image Classification (Article on Medium)

This is a induction motor faults detection project implemented with Tensorflow. We use Stacking Ensembles method (with Random Forest, Support Vector Machine, Deep Neural Network and Logistic Regression) and Machinery Fault Dataset dataset available on kaggle.

The process of combining different machine Algorithms so as to decrease variance,bias in Oder to improve prediction

An ensemble of plasmid classification tools

Ensemble of convolutional neural networks for transcriptional classification