Model.aic_classify

Model.aic_classify(classifier, pFilename, part_collection, certainity_ratio=0.8)

This function classifies parts by predicting their label and creating part sets. Labels are assigned to all parts selected for classification even if some of them have no obvious similarities to the original manually assigned label contents used for training.

Parameters:

• classifier (hwString) – The name of the classifier, i.e. the name of the folder containing the file defined in trained_file_name.

• pFilename (hwString) – The trained model, i.e. the file containing the training data.

• part_collection (Collection) – The collection containing the part entities to be classified.

• certainity_ratio (double) – Valid values between 0 and 1.

Example

Classify parts ID 104, 152, and 1858 using the CarDemo classifier and CarDemo_1.aic trained model

import hm
import hm.entities as ent

model = hm.Model()

part_col = hm.Collection(model,ent.Part,"id=104,152,1858")

model.aic_classify(
    classifier="CarDemo",
    pFilename="CarDemo_1.aic",
    part_collection=part_col,
)