setup and create model function in anomaly detection in pycaret
This recipe explains the setup and create model function in anomaly detection in pycaret. The Setup function initializes the training environment and creates the transformation pipeline and the Create model function trains and evaluates the performance of a given library.
Recipe Objective - What is the setup, create_model function in anomaly detection in pycaret?
PyCaret provides the setup and create_model function in the anomaly detection module.
Table of Contents
Links for the more related projects:-
https://www.projectpro.io/projects/data-science-projects/deep-learning-projects
https://www.projectpro.io/projects/data-science-projects/neural-network-projects
Setup function with Example:-
PyCaret provides "pycaret.anomaly.setup()" function. The Setup function initializes the training environment and creates the transformation pipeline.
from pycaret.datasets import get_data
anmly = get_data('anomaly')
# importing anomaly module
from pycaret.anomaly import *
# initialize the setup
setup_name = setup(data = anmly)
create_model function with Example:-
PyCaret provides "pycaret.anomaly.create_models()" function. The Create model function trains and evaluates the performance of a given library.
The output of this function is a scoring grid with CV scores by fold.
from pycaret.datasets import get_data
anmly = get_data('anomaly')
# importing anomaly module
from pycaret.anomaly import *
# initialize the setup
setup_name = setup(data = anmly)
# Knn model
knn = create_model('knn')
knn
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