Detecting Fraud in Digital Transactions: A Machine Learning Approach Using Logistic Regression —…

1. 1Collect a dataset of digital transactions with labeled fraud examples
2. 2Preprocess the data by handling missing values and scaling numeric features
3. 3Split the data into training and testing sets
4. 4Train a logistic regression model on the training data to predict fraud
5. 5Evaluate the model's performance using metrics such as accuracy and precision

Data scientists and analysts can benefit from this approach to improve fraud detection in digital transactions, while product managers can use it to inform product development and reduce risk

💡 Logistic regression can be used to detect fraud in digital transactions by predicting the probability of a transaction being fraudulent

Detect fraud in digital transactions with machine learning and logistic regression!