Implementation questions about machine learning algorithms.
def gradient(X_norm,y,theta,alpha,m,n,num_it): temp=np.array(np.zeros_like(theta,float)) for …
python numpy machine-learning linear-regression gradient-descentI wrote a confusion matrix calculation code in Python: def conf_mat(prob_arr, input_arr): # confusion matrix conf_arr = [[0, 0], [0, 0]] …
python machine-learningI'm using linear_model.LinearRegression from scikit-learn as a predictive model. It works and it's perfect. I have a problem …
python machine-learning scikit-learn linear-regression predictionANN (Artificial Neural Networks) and SVM (Support Vector Machines) are two popular strategies for supervised machine learning and classification. It's …
machine-learning neural-network classification svmI have Keras installed with the Tensorflow backend and CUDA. I'd like to sometimes on demand force Keras to use …
python machine-learning tensorflow kerasI have an example of a neural network with two layers. The first layer takes two arguments and has one …
python machine-learning keras neural-networkIn the following TensorFlow function, we must feed the activation of artificial neurons in the final layer. That I understand. …
tensorflow machine-learning neural-network deep-learning cross-entropyHow do I save a trained Naive Bayes classifier to disk and use it to predict data? I have the …
python machine-learning scikit-learn classificationCan anyone tell me why we set random state to zero in splitting train and test set. X_train, X_…
python random machine-learning scikit-learnI want to make a simple neural network which uses the ReLU function. Can someone give me a clue of …
python numpy machine-learning neural-network