The logistic regression algorithm uses a logistic function, also known as the sigmoid function, to map the output of a linear regression model to a probability value between 0 and 1. The sigmoid function is def
the logistic mapIn this study, we improve the pseudo-random number generation algorithm of Java based on the logistic map. We replace the seed of the random generation algorithm with a sequence of numbers which is generated by the original logistic map and the improved logistic map. And then ...
Generalized logistic mapRobustness, computational complexityThe proliferation of information and communication technology has made exchange of information easier than ever. Security and copyright protection of multimedia contents in such a scenario has become......
relationship betweentheindependentvariablesandthedependentvariable. Inlogisticregression, we use... functions to describe howtheindependentvariablesmap tothedependentvariable. Here areafew ML学习笔记 (2) asimpler way to writethecost function Algorithm looks identical tolinearregression, but...Multivariatelinea...
15 different images usually used in image processing benchmarking were used for testing the algorithm capabilities and experiments show that our proposed ... M Mostafa,MW Fakhr - 《Ssrn Electronic Journal》 被引量: 0发表: 2018年 Technological Developments in Networking, Education and Automation and...
Linear Regression is one of the most simple Machine learning algorithm that comes under Supervised Learning technique and used for solving regression problems. It is used for predicting the continuous dependent variable with the help of independent variables. ...
In order for the features to be used by a machine learning algorithm, the features are transformed and put into Feature Vectors, which are vectors of numbers representing the value for each feature. Below a VectorAssembler is used to transform and return a new DataFrame with al...
// Run training algorithm to build the model val model = new LogisticRegressionWithLBFGS() .setNumClasses(10) .run(training) // Compute raw scores on the test set. val predictionAndLabels = test.map { case LabeledPoint(label, features) => ...
The main aim of this study is to use weights of evidence (WoE), logistic regression (LR), naïve Bayes (NB), and alternating decision tree (ADTree) models to draw a landslide susceptibility map in Yanchuan County, China. First, 311 landslide points were identified through historical data,...
Linear Regression is one of the most simple Machine learning algorithm that comes under Supervised Learning technique and used for solving regression problems. It is used for predicting the continuous dependent variable with the help of independent variables. ...