本文内容 构造函数 属性 CLASSIFICATION DATA EXPLAIN EXPLAINER FUNCTION GLOBAL HAN IS_ENG IS_RAW LIME LOCAL METHOD MIMIC MODEL MODEL_CLASS MODEL_TASK PFI REGRESSION SHAP SHAP_DEEP SHAP_GPU_KERNEL SHAP_KERNEL SHAP_LINEAR SHAP_TREE TABULAR ...
(hidden groupings), and anomalies. Segments are leaf nodes containing data classification rules for the node's data value in the data that correlate and predict outcome values for the selected attribute. Anomalies are outliers or unexpected results for the data model used to Explain the attribute...
6.1. Pass your model, X_Data and Y_Data into the explainx_modules function. explainx_modules.ai(model,X_test,Y_test) As an upgrade, we have eliminated the need to pass in the model name as explainX is smart enough to identify the model type and problem type i.e. classification or...
Grad-CAM for AlexNet to explain the reason of classification (https://github.com/mathworks/Grad-CAM-for-AlexNet-to-explain-the-reason-of-classification/releases/tag/1.0.1), GitHub. Retrieved April 6, 2025. Requires MATLAB Computer Vision Toolbox Deep Learning Toolbox Image Pro...
@inproceedings{lou2012intelligible, title={Intelligible models for classification and regression}, author={Lou, Yin and Caruana, Rich and Gehrke, Johannes}, booktitle={Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining}, pages={150--158}, year={2012...
Classification of bond types by clustering analysis on phase diagrams In Fig. 2e–g, we have explored the model parameter space to identify regions that correspond to slip-only bonds and catch-slip bonds. Here we examined whether, and if so, how parameters that best-fit different experimental ...
scoreMap= imageLIME(net,X,channelIdx)uses the locally-interpretable model-agnostic explanation (LIME) technique to compute a map of the importance of the features in the input imageXwhen the networknetevaluates the activation score for the channel given bychannelIdx. For classification tasks, spec...
(2022). CAIPI in Practice: Towards Explainable Interactive Medical Image Classification. In: IFIP International Conference on Artificial Intelligence Applications and Innovations, Springer, pp 389–400 Sokol, K., & Flach, P. (2018). Glass-box: explaining ai decisions with counterfactual statements ...
We use classification analysis to study abnormalities in the data which is further used to explain the outcome of machine learning model. The ML method used to demonstrate the ideas is two class classification problem. We validate the proposed framework using a real world machine learning task: ...
Clustering and classification both are the data mining techniques where clustering is used to unsupervised learning and classification is used to supervised learning. Answer and Explanation:1 Difference between clustering and classification: Clustering: It is a method of organizing the data in a group ...