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__init__(self,
classifier=' libsvmmulticlass ' ,
classifier_options=None,
kernel=' GaussianKernel ' ,
kernel_options=None,
num_threads=' autodetect ' ,
input_dim=None,
dtype=None)
Keyword arguments: |
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classify(self,
x)
Classify the input data 'x'... |
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set_classifier(self,
name=' libsvm ' )
Sets and initialises the classifier. |
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set_kernel(self,
name,
options=None)
Sets the Kernel along with options. |
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training_set(self,
ordered=False)
Shows the set of data that has been inserted to be trained. |
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Inherited from svm_nodes._SVMNode :
is_invertible ,
train
Inherited from svm_nodes._SVMNode (private):
_check_train_args ,
_normalize_labels ,
_set_input_dim ,
_set_output_dim ,
_train
Inherited from object :
__delattr__ ,
__getattribute__ ,
__hash__ ,
__new__ ,
__reduce__ ,
__reduce_ex__ ,
__setattr__
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__call__(self,
x,
*args,
**kargs)
Calling an instance of Node is equivalent to call
its 'execute' method. |
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_refcast(self,
x)
Helper function to cast arrays to the internal dtype. |
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copy(self,
protocol=-1)
Return a deep copy of the node. |
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execute(self,
x,
*args,
**kargs)
Process the data contained in 'x'. |
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inverse(self,
y,
*args,
**kargs)
Invert 'y'. |
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is_trainable(self)
Return True if the node can be trained, False otherwise. |
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is_training(self)
Return True if the node is in the training phase,
False otherwise. |
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save(self,
filename,
protocol=-1)
Save a pickled serialization of the node to 'filename'. |
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set_dtype(self,
t)
Set internal structures' dtype. |
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