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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Goal
Building a model with other types for features in PredicSis.ai GUI using the Python SDK
Prerequisites
PredicSis.ai Python SDK (pip install predicsis; documentation)
A predictive model available on your PredicSis.ai instance
Jupyter (see http
Step1:  Choose your project
Step2:  Retrieve and describe the frame
First, pick the default schema of the project. New models can be built from the modified default schema.
Step3:  Change type of a native feature (from the central table)
Pick the frame which includes the feature you want to change the type.
Step4:  Change the type of your feature using set_categorical() or set_numerical() methods.
Step5:  Type is modified.
A model has to be build again from the default schema.
Step6:  Same for features from a peripheral table
Step7:  Type has been changed, a new model has to be builed from the default schema. To consider the change in the peripheral table, a number of aggregates has to be requested.
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Python Code:
# Load PredicSis.ai SDK
from predicsis import PredicSis
Explanation: Goal
Building a model with other types for features in PredicSis.ai GUI using the Python SDK
Prerequisites
PredicSis.ai Python SDK (pip install predicsis; documentation)
A predictive model available on your PredicSis.ai instance
Jupyter (see http://jupyter.org/)
End of explanation
pj = PredicSis.project('Outbound Mail Campaign')
Explanation: Choose your project
End of explanation
dflt_schm = pj.default_schema()
dflt_schm.describe()
Explanation: Retrieve and describe the frame
First, pick the default schema of the project. New models can be built from the modified default schema.
End of explanation
master_frame=dflt_schm.frame('Customers')
master_frame.describe()
Explanation: Change type of a native feature (from the central table)
Pick the frame which includes the feature you want to change the type.
End of explanation
master_frame.set_categorical('region_code')
master_frame.describe()
Explanation: Change the type of your feature using set_categorical() or set_numerical() methods.
End of explanation
mdl = dflt_schm.fit('model with categorical region_code')
mdl.central().describe()
Explanation: Type is modified.
A model has to be build again from the default schema.
End of explanation
email = dflt_schm.frame('Email')
email.describe()
email.set_categorical('nb_of_days_since_event')
email.describe()
Explanation: Same for features from a peripheral table
End of explanation
mdl2 = dflt_schm.fit('Model with type change in email frame',nb_aggregates=50)
mdl2.central().describe()
Explanation: Type has been changed, a new model has to be builed from the default schema. To consider the change in the peripheral table, a number of aggregates has to be requested.
End of explanation
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