Implementation questions about machine learning algorithms.
I've been reading some things on neural networks and I understand the general principle of a single layer neural network. …
math machine-learning neural-network deep-learningI have a binary prediction model trained by logistic regression algorithm. I want know which features(predictors) are more important …
python machine-learning scikit-learn logistic-regressionI'm using R package randomForest to do a regression on some biological data. My training data size is 38772 X 201. I …
r statistics machine-learning regression random-forestIs there a rule of thumb (or set of examples) to determine when to use genetic algorithms as opposed to …
artificial-intelligence machine-learning neural-network genetic-algorithmDoes tensorflow have something similar to scikit learn's one hot encoder for processing categorical data? Would using a placeholder of …
python machine-learning neural-network tensorflowConsidering the example code. I would like to know How to apply gradient clipping on this network on the RNN …
python tensorflow machine-learning keras deep-learningWhen we have a high degree linear polynomial that is used to fit a set of points in a linear …
machine-learning data-mining regressionI've trained a Linear Regression model with R caret. I'm now trying to generate a confusion matrix and keep getting …
r machine-learning artificial-intelligence classification linear-regressionRegression algorithms seem to be working on features represented as numbers. For example: This data set doesn't contain categorical features/…
python machine-learning regression linear-regression feature-selectionI am copying the pyspark.ml example from the official document website: http://spark.apache.org/docs/latest/api/python/…
apache-spark machine-learning pyspark distributed-computing apache-spark-ml