{"repo":"Rpita623/Detecting-Credit-Card-Fraud","free":true,"listed":false,"github":"https://github.com/Rpita623/Detecting-Credit-Card-Fraud","clone":"git clone https://github.com/Rpita623/Detecting-Credit-Card-Fraud.git","description":"Using R and machine learning to build a classifier that can detect credit card fraudulent transactions.","language":"R","stars":22,"topics":["data","data-science","datascience","data-analysis","data-visualization","data-modeling","data-exploration","data-manipulation","logistic-regression","decision-trees"],"license":null,"category":"machine-learning","readme_excerpt":"Detecting Credit Card Fraud This is a data science project with machine learning in R. Aim of Project The aim of this R project is to build a classifier that can detect credit card fraudulent transactions. I used a variety of machine learning algorithms like Decision Trees, Logistic Regression, Artificial Neural Networks and finally, Gradient Boosting Classifier that will be able to discern fraudulent from non-fraudulent ones. Dataset used For carrying out the credit card fraud detection, I used the Card Transactions dataset that contains a mix of fraud as well as non-fraudulent transactions. Data Exploration First I imported the datasets that contain transactions made by credit cards. I then explored the data that is contained in the dataframe. After displaying the using the function as well as the function, I proceeded to explore the other components of this dataframe. Data Manipulation In this section of the project, I scaled the data using the function. I applied this to the amount component of our amount. With the help of scaling, the data is structured according to a specified range. Therefore, there are no extreme values in the dataset that might interfere with the functioning of the model. Data Modelling After standardizing the entire dataset, I split the dataset into training set as well as test set with a split ratio of . This means that 80% of the data will be attributed to the whereas 20% will be attributed to the . I then found the dimensions using the function. ","default_branch":null,"files":null,"tree":[],"storefront":"/r/Rpita623","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Rpita623/Detecting-Credit-Card-Fraud/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}