home-credit-default-risk | Default risk prediction for Home Credit | Machine Learning library
kandi X-RAY | home-credit-default-risk Summary
kandi X-RAY | home-credit-default-risk Summary
Many people struggle to get loans due to insufficient or non-existent credit histories. And, unfortunately, this population is often taken advantage of by untrustworthy lenders. Home Credit strives to broaden financial inclusion for the unbanked population by providing a positive and safe borrowing experience. In order to make sure this underserved population has a positive loan experience, Home Credit makes use of a variety of alternative data--including telco and transactional information--to predict their clients' repayment abilities. While Home Credit is currently using various statistical and machine learning methods to make these predictions, they're challenging Kagglers to help them unlock the full potential of their data. Doing so will ensure that clients capable of repayment are not rejected and that loans are given with a principal, maturity, and repayment calendar that will empower their clients to be successful.
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Top functions reviewed by kandi - BETA
- Fte example
- Saves training and test data to a cache file
- Load training and test set
- Fteales channels
- Return the average number of appearance
- Fetch categoricals
- Encodes categoricals
- Compute the classification output
- Compute the importance of each feature
- Extract features from a dataframe
- Convert a list of transformers into a pipeline
- Wrapper for feature transformation
- Convenience function for feature selection
- Set up the logger
- Validate the dataset
- Cross validation
- Fetches missing training and test data
- Computes the Fte cash curve
- Calculate Fte cash flow rate and test
- Compute previous training
- Compute the previous credit
- Fte weights calculation
- Compute the FTE credit and test suite
- Delete keys from a cache file
home-credit-default-risk Key Features
home-credit-default-risk Examples and Code Snippets
Community Discussions
Trending Discussions on home-credit-default-risk
QUESTION
I'm writing a notebook using this data from Kaggle. Here's a screenshot of the two tables just to show we have ID columns in both.
Here's my code when trying to set up the Entity Set and add a relationship.
...ANSWER
Answered 2022-Feb-04 at 13:41If you are adding a relationship to an EntitySet
by passing in a Relationship
object, you need to make sure to use the relationship
keyword in your call like this:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install home-credit-default-risk
You can use home-credit-default-risk like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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