Implementation questions about machine learning algorithms.
I'm following a tutorial about machine learning basics and there is mentioned that something can be a feature or a …
machine-learning artificial-intelligenceI'm working on a classification problem with unbalanced classes (5% 1's). I want to predict the class, not the probability. In …
python machine-learning classification scikit-learnI am playing with a ANN which is part of Udacity DeepLearning course. I have an assignment which involves introducing …
machine-learning neural-network tensorflow deep-learning regularizedIn the MNIST beginner tutorial, there is the statement accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float")) tf.cast …
python numpy machine-learning mean tensorflowI noticed that LSH seems a good way to find similar items with high-dimension properties. After reading the paper http://…
c machine-learning hashmap nearest-neighbor locality-sensitive-hashCould you please explain what the "fit" method in scikit-learn does? Why is it useful? I am new in Machine …
python machine-learning scikit-learnIm following some lectures from lynda.com about deep learning using Keras-TensorFlow in a PyCharmCE enviroment and they didnt had …
image-processing machine-learning kerasI have asked a question a few days back on how to find the nearest neighbors for a given vector. …
algorithm language-agnostic search machine-learning nearest-neighborI've trained a tree model with R caret. I'm now trying to generate a confusion matrix and keep getting the …
r machine-learning classification r-caretOn the link of XGBoost guide: After training, the model can be saved. bst.save_model('0001.model') The model …
python machine-learning save xgboost