Back to list

Azure Machine Learning Studio

  • Data-Classification
  • Prediction
  • Exploratory analysis
  • R-language
  • Azure ML
  • Data cleansing

Analysis of the loan returns probability using Azure ML

In this project, Azure machine learning platform was used to analyze the probabilities of the client to return a loan based on his personal information and specific parameters of the loan.

First, the dataset with information on the credit status was statistically and visually analyzed in order to select an optimal evaluation strategy. The following procedures were performed:

  • a number of steps for data cleaning was evaluated,
  • detection of the erroneous fields and typos along with recovery of the missing parameters based on the available distribution.
  • On the next stage, after appropriate parameters representation and application of the outlier detection techniques based on one-class SVM model non-linear classification model were trained.

    Finally, machine learning experiment was converted into a web service, and prediction accuracy was estimated on different datasets with similar distribution parameters.

    7718815c49fffa98f3f7f88e3ff397593d4fefc2.jpg
    518b00db0e030b5d096ccef5edb9a40feb90a02a.jpg
    43050d2fe617e52bedbfcc959880feee849a1b18.jpg
    f6420204dd821b9f84ef82a0629553a9d9adc891.jpg
    Services
    Development time
    1 week of 1 developer