Decision tree function and SVM function
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I used decision function and SVM function to train the same dataset and then used them to predict the same test data set. The results showed that SVM has higher recall while DT has higher precision. There are also differences in the false positive and false negetive which I`m not sure what the cause is. Could anyone please tell me the potential causes of this maybe regarding the natural characteristics of these two functions.
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