Multiple Model Ensembling
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Updated
Apr 4, 2017 - Python
Multiple Model Ensembling
A Machine Learning Library aiming to provide reliable ensemble classifiers
Detection of Object-Based Forgery in Advanced Video
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
Data analysis on Kaggle competition Porto-Seguro
The process of combining different machine Algorithms so as to decrease variance,bias in Oder to improve prediction
Predictive lead scoring for corporate loan data
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…
Data Science Case Study
Used ensemble methods such as boosting, voting, Bagging
Finding Donor for CharityML - Machine Learning Nanodegree from Udacity
The project is about outlier detection with different methods same as FastVOA, Kmeans, DBScan or LOF, conducted on KDD dataset.
Ensemble-Voting
Predict donors using supervised learning, ensemble methods and data science
This repository contains the edited code files and the corresponding data-set for the projects available at: https://github.com/hal3/ciml
Spam Detection – Cluster SMS messages to “Spam” and “Ham” (Kaggle Challenge)
Udacity capstone project | Credit card fraud prediction | Supervised Learning | Ensemble model | Data Sampling
Code for Information Retrieval project @ University of Milan
Kernels for machine learning problems
Python 3 implementation of PAC-Bayes tree
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