Using Machine Learning to Identify Fraud in the Enron Corpus
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Updated
Nov 30, 2016 - Python
Using Machine Learning to Identify Fraud in the Enron Corpus
📧 💰 Python + Machine Learning / I analyse the Enron Scandal data and try to predict those who were involved in the Enron fraud based on their financial data
My Machine Learning First Project on Github
Gender Classification based on height, weight and shoe size using different Machine Learning Algorithms
Text Classification
ID3 Decision Tree Classifier for Machine Learning along with Reduced Error Pruning and Random Forest to avoid overfitting
a decision tree based on ID3 algorithm
Data Preprocessing Template
Predict conversion rate and generate ideas to improve conversion rate
Movie Sentiment predictor using decision tree classifier and random forests.
This project includes implementation of supervised machine learning algorithms in R language.
Linear Discriminant Tree in jupyter notebook
Enron fraud detect classifier using Decision tree algorithm
My implementation of homework 3 for the Introduction to Machine Learning class in NCTU (course number 1181).
different NN models for classify images
Implementation of Decision tree learning algorithm with chi-square pruning
Analysis and Prediction of Poker Hand Strength
Demonstration of vectorization of movies, recommendation using collaborative filtering and classification.
Various Classification models used are Logistic regression, K-NN, Support Vector Machine, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification using Python
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