PCA

Credit Card Fraud Detection

Objective Our goal is to train a Neural Network to detect fraudulent credit card transactions in a dataset referring to two days transactions by european cardholders. Source: https://www.kaggle.com/mlg-ulb/creditcardfraud/data Data credit = read.csv(path) The datasets contains transactions made by credit cards in September 2013 by european cardholders. This dataset presents transactions that occurred in two days. As we can see, this dataset consists of thirty explanatory variables, and a response variable which represents whether a transation was a fraud or not.

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German Credit and Regression Tree

Objetive Train a model and use to make predictions for German Credit dataset Data german = read.csv(path) str(german) ## 'data.frame': 1000 obs. of 21 variables: ## $ default : int 0 1 0 0 1 0 0 0 0 1 ... ## $ account_check_status : Factor w/ 4 levels "< 0 DM",">= 200 DM / salary assignments for at least 1 year",..: 1 3 4 1 1 4 4 3 4 3 .

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