SimpleSVM#
- class pyopenms.SimpleSVM#
Bases:
objectCython implementation of _SimpleSVM
- Original C++ documentation is available here
– Inherits from [‘DefaultParamHandler’]
Methods
Overload:
getDefaults(self)Returns the default parameters
getFeatureWeights(self, feature_weights)Returns the weights used for features (predictors) in the SVM model
getName(self)Returns the name
getParameters(self)Returns the parameters
getSubsections(self)predict(self, predictions, indexes)Predict class labels (and probabilities)
setName(self, in_0)Sets the name
setParameters(self, param)Sets the parameters
writeXvalResults(self, path)- getFeatureWeights(self, feature_weights: Dict[bytes | str | String, float]) None#
Returns the weights used for features (predictors) in the SVM model
Currently only supported for two-class classification If a linear kernel is used, the weights are informative for ranking features
- getSubsections(self) List[bytes]#
- predict(self, predictions: List[SVMPrediction], indexes: List[int]) None#
Predict class labels (and probabilities)
- Parameters:
predictions – Output vector of prediction results (same order as ``)
indexes – Vector of observation indexes for which predictions are desired. If empty (default), predictions are made for all observations