data-science-toolkit
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Data Science Toolkit (DST) is a Python library that helps implement data science related project with ease.
Data Science Toolkit (DST) is a Python library that helps implement data science related project with ease.
from data_science_toolkit.dataframe import DataFrame
from data_science_toolkit.model import Model
data = DataFrame()
data.load_dataset('iris')
y = data.get_column('target')
data.drop_column('target')
# decision tree model
model = Model(data_x=data.get_dataframe(), data_y=y, model_type='dt', training_percent=0.8)
# train the model
model.train()
# get all classification evaluation metrics
model.report()
#get the cross validation
model.cross_validation(5)
More information can be found on the DST documentation site.
Contrubution and suggestions are welcome via GitHub Pull Requests.
We're actively enhacing the repo with new algorithms.
FAQs
Data Science Toolkit (DST) is a Python library that helps implement data science related project with ease.
We found that data-science-toolkit demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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