1.主界面:运行skgui_modify20170104v3_feature.py; 2.点击train按钮,选择train_label.csv文件,设置参数,点击fit按钮完成训练过程; 3.点击example按钮,选择example文件中的任意csv文件,点击Show按钮,可以显示speed和occupacy; 4.点击predict按钮,预测选择文件的检测结果,结果会被写入到listtemp.csv中; 5.预测完成多个example文件夹中的文件后,点击list,选择listtemp.csv,点击Calculate按钮,可以显示准确率和平均检测时间,并画出混淆矩阵。
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