qiskit.aqua.components.multiclass_extensions.ErrorCorrectingCode¶
-
class
ErrorCorrectingCode(code_size=4)[ソース]¶ The Error Correcting Code multiclass extension.
Error Correcting Code (ECC) is an ensemble method designed for the multiclass classification problem. As for the other multiclass methods, the task is to decide one label from \(k > 2\) possible choices.
Class
Code Word
\(f_0\)
\(f_1\)
\(f_2\)
\(f_3\)
\(f_4\)
\(f_5\)
1
0
1
0
1
0
1
2
1
0
0
1
0
0
3
1
1
1
0
0
0
The table above shows a 6-bit ECC for a 3-class problem. Each class is assigned a unique binary string of length 6. The string is also called a codeword. For example, class 2 has codeword
100100. During training, one binary classifier is learned for each column. For example, for the first column, ECC builds a binary classifier to separate \(\{2, 3\}\) from \(\{1\}\). Thus, 6 binary classifiers are trained in this way. To classify a new data point \(\mathbf{x}\), all 6 binary classifiers are evaluated to obtain a 6-bit string. Finally, we choose the class whose bitstring is closest to \(\mathbf{x}\)’s output string as the predicted label. This implementation of ECC uses the Euclidean distance.- パラメータ
code_size (
int) – Size of error correcting code
Methods
__init__([code_size])- type code_size
int
predict(x)Applying multiple estimators for prediction.
set_estimator(estimator_cls[, params])Called internally to set
Estimatorand parameters :type estimator_cls:Callable[[List],Estimator] :param estimator_cls: AnEstimatorclass :type params:Optional[List] :param params: Parameters for the estimatortest(x, y)Testing multiple estimators each for distinguishing a pair of classes.
train(x, y)Training multiple estimators each for distinguishing a pair of classes.
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predict(x)[ソース]¶ Applying multiple estimators for prediction.
- パラメータ
x (numpy.ndarray) – NxD array
- 戻り値
predicted labels, Nx1 array
- 戻り値の型
numpy.ndarray
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set_estimator(estimator_cls, params=None)¶ Called internally to set
Estimatorand parameters :type estimator_cls:Callable[[List],Estimator] :param estimator_cls: AnEstimatorclass :type params:Optional[List] :param params: Parameters for the estimator- 戻り値の型
None