Category: Big Data Analysis

Precision Medicine Benefits

Precision medicine benefits are possible when medical decisions are based on of individual patients. The fundamental idea of this data-driven medical approach is described in our article on precision medicine. This article lists six...

Precision Medicine Stratified Medicine P4 Medicine Personalized Medicine Molecular Biomarkers Behavioral Biomarkers Patients Medical Decisions Predictive

Precision Medicine

Precision medicine is a data-driven medical approach that bases medicial decisions on invididual patients by using and individual patient characteristics. The approach is also called stratified medcine or personalized medicine. Some also call it...

Biomarkers Stratisfy Patients Measurable Quantity of Data Genomic alterations Molecular Markers Behavioral Disease Severity Scores Lifestyle Characteristics

Biomarkers

Biomarkers stand for any measurable quantity of big data or score that is used to stratify patients. In other words, stratifying patients mean in this context to arrange or classify them into well-defined risk...

Autoencoder Deep Learning Encoder Decoder Architecture Dimensionality Reduction Technique Unsupervised Learning Denoising Autoencoder High Dimensions

Autoencoder

Autoencoder refers to an unsupervised learning technique that is often used in the context of dimensionality reduction of big data. It projects some data from a higher dimension to a lower dimension via linear...

Dimensionality Reduction Techniques Convolutional Neural Network Principle Component Analysis PCA CNN Deep Learning Machine Learning Methods Algorithms

Dimensionality Reduction Techniques

Dimensionality reduction techniques are methods to reduce the dimensionality of a modeling problem. This is very important when working with big data and high-dimensional data sets. Learning from this data is a very challenging...

Activation Function Neural Network Deep Learning Rectified Linear Unit ReLU tanh Sigmoid Nonlinear Activation Function Output Logistic Activation Function

Activation Function

Activation function refers to specific function used in a neural network node that is used to compute the output of this node given a specific node input. Computing this function has more impact recently...

ReLU Neural Network Rectified Linear Unit Rectifier Activation Function Artificial Neural Networks Deep Learning Ramp Function Nonlinear Activation Function

ReLU Neural Network

ReLU Neural Network is a well known phrase that stands for the Rectified Linear Unit (ReLU) activation function used more recently during the training of neural networks and deep learning networks used with big...

tanh hyperbolic tangent function activation function rescaled logistic sigmoid neural network deep learning nonlinear activation function non-linear

tanh

Tanh stands for hyperbolic tangent function and it is often used as a non-linear activation function in machine learning algorithms when working with big data. The particular interesting property of this function is that...

GGPLOT2 Tutorial R Package Examples Graphics Line Plot Function Draw Graph Statistical Computing with R GGPLOT Axis Labels Figure Legend Lattice Tanh

GGPLOT2 Tutorial

GGPLOT2 tutorial refers to this short tutorial on using the ggplot2 package of the statistical computing with R tool in order to create simple plots of functions. A wide variety of machine learning algorithms...