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

Detection of Object-Based Forgery in Advanced Video

Multiple Model Ensembling

This notebook investigates whether multiple CNN models can achieve higher classification accuracy than any individual model.

Machine Learning codes

The project is about outlier detection with different methods same as FastVOA, Kmeans, DBScan or LOF, conducted on KDD dataset.

Used ensemble methods such as boosting, voting, Bagging

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

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 equivalence between pairs of questions using a dataset released by Quora. We explore different approaches involving using different classifiers with a rich feature set, a Siamese Neural Network which uses an LSTM, and an ensemble of the multiple approaches. Our ensemble model outperforms the classifier and Siamese models.

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

Predict donors using supervised learning, ensemble methods and data science

Python 3 implementation of PAC-Bayes tree

Data Science Case Study

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

Predictive lead scoring for corporate loan data

Finding Donor for CharityML - Machine Learning Nanodegree from Udacity

Classification model to predict if the client will subscribe to a term deposit based on the given bank dataset

A Machine Learning Library aiming to provide reliable ensemble classifiers

Built an Ensemble Classifier for predicting the income levels of a population on the basis of demographics data

[CSED426] Big Data Homework - 2017 Fall

An implementation of an Ensemble classifier of Linear classifiers using multiple processes

Automate the loan eligibility process (real time) based on customer detail provided while filling online application form. These details are Gender, Marital Status, Education, Number of Dependents, Income, Loan Amount, Credit History and others.

Predictive Analysis of detecting signal emitting Source

Code for Information Retrieval project @ University of Milan

Built Random Forest and GBDT using XGBOOST model on Amazon fine food review dataset

Visualizing an XGBoost model in R using a sunburst plot (using inTrees)

Kernels for machine learning problems

Skin Lesion Analysis Towards Melanoma Detection