LinearToProbabilities¶
Convert linear predictions to (two-class) pseudo-probabilities.
This node can be chained after e.g., ApplyLinearTransform if that node is meant to implement a linear classifier. The resulting data format is then the same as generated by the other classification nodes. Note that this node assumes that your linear scores are signed, i.e., negative scores encode that the first or negative class ("class 0") is more probable and positive scores encode that the second or positive class ("class 1") is more probable, and that they are in a somewhat reasonable range (e.g., the two class means mapping to -1 and +1). The resulting scores will be in a 0-1 range and somewhat behave like probabilities, but be aware that they will not be properly calibrated and thus this procedure should be viewed as a cheap "trick" to get probabilities. For an accurate transformation, use the Probability Calibration node instead. More Info... Version 0.8.0
Ports/Properties¶
data¶
Data to process.
replace_axis¶
Replace prior feature axis (if applicable). This will check if the data contains a prior one-element (i.e., dummy) feature axis and replace it with the new two-class axis. This can be necessary for downstream nodes to recognize the output as well-formed two-class probabilistic predictions.
set_breakpoint¶
Set a breakpoint on this node. If this is enabled, your debugger (if one is attached) will trigger a breakpoint.
metadata¶
User-definable meta-data associated with the node. Usually reserved for technical purposes.