casm.learn.TrainingData¶
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class
casm.learn.TrainingData(input, verbose=True)[source]¶ TrainingData is a data structure used to collect data from the training data file.
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filename¶ The name of the training data file
- Type
str
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filetype¶ The data format of the training data file
- Type
str, one of [“selection”, “csv”, “json”]
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X_name¶ The name of the X columns in the training data file
- Type
str
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X¶ The training input samples (correlations).
- Type
array-like of shape (n_samples, n_features)
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y_name¶ The name of the y column in the training data file
- Type
str
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y¶ The target values (property values).
- Type
array-like of shape: (n_samples, 1)
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n_samples¶ The number of samples / target values (number of rows in X)
- Type
int
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n_features¶ The number of features (number of columns in X)
- Type
int
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sel¶ The selection specifying the training data
- Type
casm.Selection, (exists if filetype==”selection”)
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data¶ Contains the X and y data
- Type
pandas.DataFrame
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hull_dist_name¶ The name of the hull_dist column in the training data file
- Type
str, (exists if weight method==”wHullDist”)
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hull_dist¶ The hull distance values.
- Type
array-like of shape: (n_samples, 1), (exists if weight method==”wHullDist”)
- Parameters
input (dict) – The input settings as a dict
verbose (boolean, optional, default=True) – Print information to stdout.
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__init__(input, verbose=True)[source]¶ - Parameters
input (dict) – The input settings as a dict
verbose (boolean, optional, default=True) – Print information to stdout.
Methods
__init__(input[, verbose])- param input
The input settings as a dict
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