Generative AutoML for Tabular Data
Project description
SapientML
Getting Started
Installation
pip install sapientml
Generate Code in a notebook
Please download housing-prices.csv to execute the following code.
import pandas as pd
df = pd.read_csv("housing-prices.csv")
from sapientml import SapientML
sml = SapientML()
ret = sml.generate_code(
training_data=df,
task_type="regression",
target_columns=["SalePrice"],
ignore_columns=["Id"],
adaptation_metric="RMSE",
hyperparameter_tuning=False,
id_columns_for_prediction=["Id"]
)
ret.save(
"outputs",
save_dev_scripts=True,
save_user_scripts=True,
save_datasets=True,
save_running_arguments=True,
)
Run Generated Code
cd outputs/
python final_script.py
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
sapientml-0.2.2.tar.gz
(19.1 kB
view hashes)
Built Distribution
sapientml-0.2.2-py3-none-any.whl
(25.6 kB
view hashes)
Close
Hashes for sapientml-0.2.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | bf448b19bb846fbe2c9b94d14474be88a69d76cb754aae48c7b65c6d13d947d8 |
|
MD5 | 55f4e4fc0f0102087a80dc9e910f159e |
|
BLAKE2b-256 | 778063c2b56657d0695e9c874b7442caac9de8b9c8df66be46492fae0cf73291 |