What is Gini Coefficient?

Gini Coefficient is a measure of statistical dispersion intended to represent the income or wealth distribution of a nation’s residents and is the most commonly used measure of inequality. The Gini coefficient measures the inequality among values of a frequency distribution (for example, levels of income). A Gini coefficient of zero expresses perfect equality, where all values are the same … Read more

What is Gaussian Distribution (Normal Distribution)?

Gaussian Distribution (Normal Distribution) in probability theory is a very common continuous probability distribution. Normal distribution is important in statistics and is often used in the natural and social sciences to represent real-valued random variables whose distributions are not known. The normal distribution is useful because of the central limit theorem. In its most general form, under some conditions (which … Read more

What is Fuzzy Clustering?

Fuzzy Clustering (also referred to as soft clustering) is a form of clustering in which each data point can belong to more than one cluster. Clustering or cluster analysis involves assigning data points to clusters (also called buckets, bins, or classes), or homogeneous classes, such that items in the same class or cluster are as similar as possible, while items … Read more

What is Feedforward Neural Network (FNN)?

Feedforward Neural Network (FNN) is a biologically inspired classification algorithm. It consists of a (possibly large) number of simple neuron-like processing units, organized in layers. Every unit in a layer is connected with units in the previous layer. These connections are not all equal: each connection may have a different strength or weight. The weights on these connections encode the … Read more

What is Feature Vector?

Feature vector in pattern recognition and machine learning is an n-dimensional vector of numerical features that represent some object. Many algorithms in machine learning require a numerical representation of objects since such representations facilitate processing and statistical analysis. When representing images, the feature values might correspond to the pixels of an image, when representing texts perhaps term occurrence frequencies. Feature … Read more

What is Feature in machine learning?

Feature in machine learning and pattern recognition is an individual measurable property of a phenomenon being observed. Choosing informative, discriminating and independent features is a crucial step for effective algorithms in pattern recognition, classification, and regression. Features are usually numeric, but structural features such as strings and graphs are used in syntactic pattern recognition. The concept of “feature” is related … Read more

What are False Negatives?

False negatives are where a test result indicates that a condition failed, while it was successful. I.e. erroneously no effect has been assumed. A common example is a guilty prisoner freed from jail. The condition: “Is the prisoner guilty?” is true (yes, the prisoner is guilty). But the test (a court of law) failed to realize this, and wrongly decided … Read more

What are False Positives?

False positives commonly called a “false alarm”, is a result that indicates a given condition has been fulfilled when it has not. I.e. erroneously a positive effect has been assumed. In the case of “crying wolf” – the condition tested for was “is there a wolf near the herd?”; the result was that there had not been a wolf near … Read more

What is Extrapolation?

Extrapolation in mathematics is the process of estimating, beyond the original observation range, the value of a variable on the basis of its relationship with another variable. It is similar to interpolation, which produces estimates between known observations, but extrapolation is subject to greater uncertainty and a higher risk of producing meaningless results. Extrapolation may also mean an extension of … Read more

What is Explanatory Data Analysis?

Explanatory Data Analysis (EDA) in statistics is an approach to analyzing data sets to summarize their main characteristics, often with visual methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling or hypothesis testing task. Exploratory data analysis was promoted to encourage statisticians to explore … Read more