nimare.base
.Estimator
- class Estimator[source]
Bases:
nimare.base.NiMAREBase
Estimators take in Datasets and return MetaResults.
All Estimators must have a
_fit
method implemented, which applies algorithm-specific methods to a dataset and returns a dictionary of arrays to be converted into a MetaResult. Users will interact with the_fit
method by calling the user-facingfit
method.fit
takes in aDataset
, calls_validate_input
, then_preprocess_input
, then_fit
, and finally converts the dictionary returned by_fit
into aMetaResult
.Methods
fit
(dataset[, drop_invalid])Fit Estimator to Dataset.
get_params
([deep])Get parameters for this estimator.
load
(filename[, compressed])Load a pickled class instance from file.
save
(filename[, compress])Pickle the class instance to the provided file.
set_params
(**params)Set the parameters of this estimator.
- fit(dataset, drop_invalid=True)[source]
Fit Estimator to Dataset.
- Parameters
- Returns
Results of Estimator fitting.
- Return type
- Variables
~Estimator.fit.inputs_ (
dict
) – Inputs used in _fit.
- classmethod load(filename, compressed=True)[source]
Load a pickled class instance from file.
- Parameters
- Returns
obj – Loaded class object.
- Return type
class object
- set_params(**params)[source]
Set the parameters of this estimator.
The method works on simple estimators as well as on nested objects (such as pipelines). The latter have parameters of the form
<component>__<parameter>
so that it’s possible to update each component of a nested object.- Return type
self