Definition of Feature A feature is a characteristic of something, often used to describe data. In machine learning, features are the variables that are used to train and predict models. Good features are important for making accurate predictions, so it is important to select the most relevant features for your data set. What is a…
Definition of Functional Programming Functional Programming: Functional programming is a style of programming in which the programmer focuses on functions instead of objects. In functional programming, functions are treated as first-class citizens, meaning they can be passed around and used like any other variable. Functional programming languages typically emphasize simplicity and purity, meaning that functions…
Definition of Function Function: A function is a set of instructions that tells a computer what to do. Functions can be used to calculate things, or to make decisions. What are Functions used for? Functions are a key component in the programming language of data science and machine learning. A function is a block of…
Definition of F-Test F-test: An F-test is a statistical test used to determine the significance of a difference between two variances. What is an F-Test used for? An F-Test is a statistical test used to compare the variability between two population variances. It is used to determine if there is a significant difference between the…
Definition of Frequentist Frequentist: A Frequentist is someone who believes that the only valid methods of statistics are those that rely on the law of large numbers, and the principle of population stabilization. What do Frequentist do? Frequentists are data scientists and machine learning specialists who use frequentist statistical methods for their work. Frequentist methods…
Definition of Frequency Table Frequency Table: A frequency table is a table that shows how often each value in a data set occurs. What are Frequency Tables used for? Frequency tables are used to display and quickly analyze the distribution of a set of data. Frequency tables display information in a tabular format that includes…
Definition of F-Measure F-Measure: F-Measure is a statistic used in machine learning to measure the effectiveness of a classification model. It is a harmonic mean of precision and recall, both of which are ratios of correct classifications to total number of classifications. What is an F-Measure used for? F-Measure is an important metric used to…
Definition of Feature Selection Feature Selection: Feature selection is the process of choosing which features (or attributes) of a data set to use in order to solve a problem. This is an important step in data science, as it can help reduce the complexity of a problem and improve the accuracy of predictions or models….
Definition of Feature Engineering Feature Engineering: Feature engineering is the process of transforming raw data into a form that is more amenable to analysis or machine learning. This can involve things like aggregating data, transforming variables, or creating new features from existing variables. Feature engineering is an important part of data science, as it can…
Definition of False Positive False Positive: False positive is a result that incorrectly identifies an event as being positive. What are False Positive used? False Positive is a term used in data science and machine learning that refers to an incorrect classification of an item as being positive when, in reality, it is negative. It…