SantanderCustomerSatisfaction
OpenML dataset with id 42395
Banco Santander
Full work available at URL: https://api.openml.org/data/v1/download/21829696/SantanderCustomerSatisfaction.arff
Upload date: 26 April 2020
Dataset Characteristics
Number of classes: 2
Number of features: 202 (numeric: 200, symbolic: 1 and in total binary: 1 )
Number of instances: 200,000
Number of instances with missing values: 0
Number of missing values: 0
Author: Banco Santander Source: Unknown - 3-04-2019 Please cite: Unknown
At Santander our mission is to help people and businesses prosper. We are always looking for ways to help our customers understand their financial health and identify which products and services might help them achieve their monetary goals. Our data science team is continually challenging our machine learning algorithms, working with the global data science community to make sure we can more accurately identify new ways to solve our most common challenge, binary classification problems such as: is a customer satisfied? Will a customer buy this product? Can a customer pay this loan?
Dataset taken from Kaggle https://www.kaggle.com/c/santander-customer-transaction-prediction/data
This page was built for dataset: SantanderCustomerSatisfaction