You are given a dataset with 500 examples, 20 features and 2 classes. the data is linearly separable, and thus, you train a linear svm using 5-fold cross validation obtaining the following results: fold 1 fold 2 fold 3 fold 4 fold 5 error 1/100 36/100 1/100 0/100 1/100 the classifier is performing very well except the 2nd fold. can you give a plausible explanation? (hint: think about the support vectors)
Answers: 1
Physics, 22.06.2019 12:00, marquez8
You have a resistor and a capacitor of unknown values. first, you charge the capacitor and discharge it through the resistor. by monitoring the capacitor voltage on an oscilloscope, you see that the voltage decays to half its initial value in 2.70 miss . you then use the resistor and capacitor to make a low-pass filter. what is the crossover frequency fc?
Answers: 2
Physics, 22.06.2019 18:00, kaylaamberd
Avector of magnitude 2 cannot be added to a vector of magnitude 3 so that the magnitude of the resultant is a. zero b. 1 c. 3 d. 5 e. 7
Answers: 1
You are given a dataset with 500 examples, 20 features and 2 classes. the data is linearly separable...
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