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#Bank Marketing Example
This page describes how to run Mahout’s SGD classifier on the UCI Bank Marketing dataset. The goal is to predict if the client will subscribe a term deposit offered via a phone call. The features in the dataset consist of information such as age, job, marital status as well as information about the last contacts from the bank.
The bank marketing example code lives under
The data can be found at
This example consists of 3 classes:
When you run the main method of BankMarketingClassificationMain it parses the dataset using the TelephoneCallParser and trains a logistic regression model with 20 runs and 20 passes. The TelephoneCallParser uses Mahout’s feature vector encoder to encode the features in the dataset into a vector. Afterwards the model is tested and the learning rate and AUC is printed accuracy is printed to standard output.