This is the trainable-object Reference Manual, version 0.1, generated automatically by Declt version 4.0 beta 2 "William Riker" on Sun Sep 15 06:55:14 2024 GMT+0.
The main system appears first, followed by any subsystem dependency.
trainable-objectProvides a metaclass and APIs for the trainable funcallable instances.
Masataro Asai
LGPL
0.1
closer-mop (system).
serializable-object (system).
package.lisp (file).
Files are sorted by type and then listed depth-first from the systems components trees.
trainable-object/trainable-object.asdtrainable-object (system).
trainable-object/package.lisptrainable-object (system).
binary-classifier (class).
classifier (class).
evaluate (generic function).
initialize-instance (method).
logical-form (generic function).
predict (generic function).
train (generic function).
trainable-object (class).
Packages are listed by definition order.
trainable-objectcloser-mop.
common-lisp.
serializable-object.
binary-classifier (class).
classifier (class).
evaluate (generic function).
logical-form (generic function).
predict (generic function).
train (generic function).
trainable-object (class).
Definitions are sorted by export status, category, package, and then by lexicographic order.
Evaluate a model, i.e., compute the loss/score function for the ground truth output and the predicted output.
trainable-object) input output &key verbose &allow-other-keys) ¶A generic function that returns a symbolic logical form that corresponds to the machine learning model. Not all ML model has a method for this function.
Predict the output using a model.
Train a model using the input / output.
INPUT / OUTPUT could be a list, if the model has multiple inputs / outputs.
When BATCH is non-nil, it assumes a batch (multiple data points) input.
The responsibility for handling this parameter properly belongs to each method.
In general, when BATCH is an INTEGER value, it is assumed to be the batch processing size.
binary-classifier) &rest args &key &allow-other-keys) ¶fixnum
2
fixnum
:classes
It represents a function-like object that is trainable from data, and is serializable so that it can save its learned parameters.
serializable-object.
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