| Name | example-package-Akalya JSON |
| Version |
0.0.1
JSON |
| download |
| home_page | |
| Summary | A small example package |
| upload_time | 2023-09-05 09:53:11 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.7 |
| license | |
| keywords |
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| VCS |
 |
| bugtrack_url |
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| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
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<<<<<<< HEAD
# mle-training
=======
# mle-training
# Median housing value prediction
The housing data can be downloaded from https://raw.githubusercontent.com/ageron/handson-ml/master/. The script has codes to download the data. We have modelled the median house value on given housing data.
The following techniques have been used:
- Linear regression
- Decision Tree
- Random Forest
## Steps performed
- We prepare and clean the data. We check and impute for missing values.
- Features are generated and the variables are checked for correlation.
- Multiple sampling techinuqies are evaluated. The data set is split into train and test.
- All the above said modelling techniques are tried and evaluated. The final metric used to evaluate is mean squared error.
## To excute the script
python < scriptname.py >
Raw data
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