Utility class to compute the transfer error of classifiers.
Functions
auc_error(predicted, target) | Computes the area under the ROC for the given the |
auto_null_dist(dist) | Cheater for human beings – wraps dist if needed with some |
ceil(x) | Return the ceiling of x as a float. |
chisquare(obs[, exp]) | Compute the chisquare value of a contingency table with arbitrary dimensions. |
corr_error(predicted, target) | Computes the correlation between the target and the predicted values. |
corr_error_prob(predicted, target) | Computes p-value of correlation between the target and the predicted |
enhanced_doc_string(item, *args, **kwargs) | Generate enhanced doc strings for various items. |
friedmanchisquare(*args) | Friedman Chi-Square is a non-parametric, one-way within-subjects |
linregress(*args) | Calculates a regression line on two arrays, x and y, corresponding to x,y pairs. |
log10 | log10(x) -> the base 10 logarithm of x. |
mean_mismatch_error(predicted, target) | Computes the percentage of mismatches between some target and some predicted values. |
mean_power_fx(data) | Returns mean power |
nanmean(x[, axis]) | Compute the mean over the given axis ignoring nans. |
relative_rms_error(predicted, target) | Ratio between RMSE and root mean power of target output. |
rms_error(predicted, target) | Computes the root mean squared error of some target and some predicted values. |
root_mean_power_fx(data) | Returns root mean power |
table2string(table[, out]) | Given list of lists figure out their common widths and print to out |
Classes
BayesConfusionHypothesis(**kwargs[, alpha, ...]) | Bayesian hypothesis testing on confusion matrices. |
ClassWithCollections(**kwargs[, descr]) | Base class for objects which contain any known collection |
ClassifierError(clf, **kwargs[, labels, train]) | Compute (or return) some error of a (trained) classifier on a dataset. |
Collectable([value, name, doc]) | Collection element. |
ConditionalAttribute(*args, **kwargs[, enabled]) | Simple container intended to conditionally store the value |
Confusion(**kwargs[, attr, labels, ...]) | Compute a confusion matrix from predictions and targets (Node interface) |
ConfusionBasedError(clf, **kwargs[, labels, ...]) | For a given classifier report an error based on internally |
ConfusionMatrix(**kwargs[, labels, labels_map]) | Class to contain information and display confusion matrix. |
ConfusionMatrixError([labels]) | Compute confusion matrix as an “error function” |
Dataset(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes. |
Node(**kwargs[, space, postproc]) | Common processing object. |
ROCCurve(labels[, sets]) | Generic class for ROC curve computation and plotting |
RegressionStatistics(**kwargs) | Class to contain information and display on regression results. |
StringIO([buf]) | class StringIO([buffer]) |
SummaryStatistics([targets, predictions, ...]) | Basic class to collect targets/predictions and report summary statistics |
Exceptions
BayesConfusionHypothesis(**kwargs[, alpha, ...]) | Bayesian hypothesis testing on confusion matrices. |
ClassWithCollections(**kwargs[, descr]) | Base class for objects which contain any known collection |
ClassifierError(clf, **kwargs[, labels, train]) | Compute (or return) some error of a (trained) classifier on a dataset. |
Collectable([value, name, doc]) | Collection element. |
ConditionalAttribute(*args, **kwargs[, enabled]) | Simple container intended to conditionally store the value |
Confusion(**kwargs[, attr, labels, ...]) | Compute a confusion matrix from predictions and targets (Node interface) |
ConfusionBasedError(clf, **kwargs[, labels, ...]) | For a given classifier report an error based on internally |
ConfusionMatrix(**kwargs[, labels, labels_map]) | Class to contain information and display confusion matrix. |
ConfusionMatrixError([labels]) | Compute confusion matrix as an “error function” |
Dataset(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes. |
Node(**kwargs[, space, postproc]) | Common processing object. |
ROCCurve(labels[, sets]) | Generic class for ROC curve computation and plotting |
RegressionStatistics(**kwargs) | Class to contain information and display on regression results. |
StringIO([buf]) | class StringIO([buffer]) |
SummaryStatistics([targets, predictions, ...]) | Basic class to collect targets/predictions and report summary statistics |