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e_out = mu * lambda + (1-LAMBDA) * (1-MU), lambda = 0.8,mu brought in to get answers(3) Answer: 0.5+0.3*s* (|theta|-1)2.17th, 18 questions(1) Test instructions:The 17th question means that in [ -1,1] take 20 points, separated into 21 intervals as the theta of the range of values, each classification has 42 hyphothesis, enumerate all the possible conditions to find the smallest hyphothesis e_in, record the smallest e_inThe 18th question means to calculate the e_out by the formula of the 16th que

(J,:)); End Outputoftest (:, m) = W2 ' *hiddentestoutput+b2;end%% result analysis% based on network output find out what kind of data belongs to m=1:400 Output_fore (m) =find (outputoftes T (:, M) ==max (Outputoftest (:, M))), END%BP Network prediction Error ERROR=OUTPUT_FORE-OUTPUT1 (n (1601:2000)) '; K=zeros (1,4); % find out which category of the inferred error belongs to which class for i=1:400 if error (i) ~=0 [B,c]=max (Testoutput (i,:)); Switch C Case 1 K (1) =k (1) +1

Before installing Scikit-learn, you need to install numpy,scipy. However, there are always errors when installing scipy (pip install scipy). After a series of lookups, the reason is that scipy relies on numpy and many other libraries (such as Lapack/blas), but these libraries are not easily accessible under Windows.After finding, the discovery can be solved by another way, http://www.lfd.uci.edu/~gohlke/pythonlibs/#numpyDownload here: Numpy-1.11

data.X = [[1.,-1., 2.], [2., 0., 0.], [0.,1.,-1.]] Binarizer= preprocessing. Binarizer (). Fit (X)#The default threshold value is 0.0PrintBinarizer#Binarizer (copy=true, threshold=0.0)Printbinarizer.transform (X)#[1.0. 1.]#[1.0. 0.]#[0.1. 0.]Binarizer= preprocessing. Binarizer (threshold=1.1)#set the threshold value to 1.1Printbinarizer.transform (X)#[0.0. 1.]#[1.0. 0.]#[0.0. 0.]4. Label preprocessing (label preprocessing)4.1) Label binary value (label binarization)Labelbinarizer is typica