Theory
The Theory class provides a high-level unified way to run data science and machine learning models.
Attributes
- Graph
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- Supertypes
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trait Serializabletrait Producttrait Equalsclass Objecttrait Matchableclass AnyShow all
Members list
Value members
Concrete methods
Perform Exploratory Data Analysis (EDA) using Simple Linear Regression y vs. x_j for each predictor variable x_j. FIX -- other more flexible options should be explored, exp. for time series
Perform Exploratory Data Analysis (EDA) using Simple Linear Regression y vs. x_j for each predictor variable x_j. FIX -- other more flexible options should be explored, exp. for time series
Value parameters
- dset
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the dataset to be explored
Attributes
Run all models in the given list.
Run all models in the given list.
Attributes
Screen/reduce the features/variables based on model agnostic dependency/correlation analysis of the predictor and response variables. Performs a quick pre-screening.
Screen/reduce the features/variables based on model agnostic dependency/correlation analysis of the predictor and response variables. Performs a quick pre-screening.
Value parameters
- mod
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the model to simplify by using fewer predictor variables
Attributes
Select the features/variables based on model QoF metrics. Requires the model to be run multiple times.
Select the features/variables based on model QoF metrics. Requires the model to be run multiple times.
Value parameters
- mod
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the model to simplify by using fewer predictor variables
- tech
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the feature selection technique to use (defaults to Backward)
Attributes
Inherited methods
An iterator over the names of all the elements of this product.
An iterator over the names of all the elements of this product.
Attributes
- Inherited from:
- Product
An iterator over all the elements of this product.
An iterator over all the elements of this product.
Attributes
- Returns
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in the default implementation, an
Iterator[Any] - Inherited from:
- Product