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服务器优惠
AI论文
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4.1. Partial dependence plots
4.1. Partial dependence plots 4.1. Partial dependence plots Partial dependence plots (PDP) show the dependence between the targetresponse 1 and a set of ‘target’ features, mar... -
2.1 Importance of Interpretability
2.1 Importance of Interpretability 2.1 Importance of Interpretability If a machine learning model performs well, why do not we just trust the model and ignore why it made a c... -
4.1. 部分依赖图
4.1. 部分依赖图 4.1. 部分依赖图 校验者: 待核验翻译者: @Loopy 部分依赖图(以下简称PDP)显示了目标响应[1]和一组“目标”特征之间的依赖关系，并边缘化所有其他特征（“补充”特征）的值。直观地，我们可以将部分依赖关系解释为预期目标响应作为“目标”特征的函数。 由于人类感知的限制，目标特征集的大小必须很小（通常是一个或两个）... -
4.1. 部分依赖图
4.1. 部分依赖图 4.1. 部分依赖图 4.1. 部分依赖图 4.1. 部分依赖图 校验者: 待核验翻译者: @Loopy 部分依赖图(以下简称PDP)显示了目标响应[1]和一组“目标”特征之间的依赖关系，并边缘化所有其他特征（“补充”特征）的值。直观地，我们可以将部分依赖关系解释为预期目标响应作为“目标”特征的函数。 由于人类感知的... -
2.5 Properties of Explanations
2.5 Properties of Explanations 2.5 Properties of Explanations We want to explain the predictions of a machine learning model. To achieve this, we rely on some explanation metho... -
4.5 Decision Rules
4.5 Decision Rules 4.5.1 Learn Rules from a Single Feature (OneR) 4.5.2 Sequential Covering 4.5.3 Bayesian Rule Lists 4.5.4 Advantages 4.5.5 Disadvantages 4.5.6 Software and A... -
Regression
Regression Assemble the Data Training a Model Regression It’s easy to think of deep learning models as being classified into domains, like computer vision, NLP, and so forth.... -
Analyze the blockchain with hyperfunctions
Analyze the blockchain with hyperfunctions Hyperfunctions for simplified statistical queries Continuous aggregates for blockchain analytics Continuous aggregate: transactions Con... -
4.4 Decision Tree
4.4 Decision Tree 4.4.1 Interpretation 4.4.2 Example 4.4.3 Advantages 4.4.4 Disadvantages 4.4.5 Software 4.4 Decision Tree Linear regression and logistic regression models...