What kind of data do you have? Pick the main type using the buttons below. Then let the decision tree guide you toward your graphic possibilities. Alternatively, check thecomplete decision tree. NumericCategoricNum & CatMapsNetworkTime series ...
layer.py importnumpyasnpclassSigmoid:defforward(self,X):return1.0/(1.0+np.exp(-X))defbackward(self,X,top_diff):output=self.forward(X)return(1.0-output)*output*top_diffclassTanh:defforward(self,X):returnnp.tanh(X)defbackward(self,X,top_diff):output=self.forward(X)return(1.0-np.square(...
linear_model import mlnn from utils import plot_decision_boundary # Generate a dataset and plot it np.random.seed(0) X, y = sklearn.datasets.make_moons(200, noise=0.20) plt.scatter(X[:,0], X[:,1], s=40, c=y, cmap=plt.cm.Spectral) plt.show() layers_dim = [2, 3, 2] ...
MURRAY MUST ACCEPTHIS PUNISHMENT Alasdair Reid reports on a good decision from a whistler prone to losing the plotAlasdair Reid
utils import train_test_split, normalize from mlfromscratch.utils import Plot, accuracy_score class NaiveBayes(): """The Gaussian Naive Bayes classifier. """ def fit(self, X, y): @@ -17,8 +16,7 @@ def fit(self, X, y): X_where_c = X[np.where(y == c)] self.parameters....
group decisionmulticriteria decision aid (MCDA)participatory evaluationCurrently, participatory evaluation processes using multicriteria decision aids are barely used in the context of contaminated sites, even though they are a powerful tool for supporting land-use decision-making. The aim of this paper ...