Fundamental analysisFundamental analysis, in accounting and finance, is the analysis of a business's financial statements (usually to analyze the business's assets, liabilities, and earnings); health; and competitors and markets. It also considers the overall state of the economy and factors including interest rates, production, earnings, employment, GDP, housing, manufacturing and management. There are two basic approaches that can be used: bottom up analysis and top down analysis.
Supervised learningSupervised learning (SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value (also known as human-labeled supervisory signal) train a model. The training data is processed, building a function that maps new data on expected output values. An optimal scenario will allow for the algorithm to correctly determine output values for unseen instances. This requires the learning algorithm to generalize from the training data to unseen situations in a "reasonable" way (see inductive bias).
Technical analysisIn finance, technical analysis is an analysis methodology for analysing and forecasting the direction of prices through the study of past market data, primarily price and volume. As a type of active management, it stands in contradiction to much of modern portfolio theory. The efficacy of technical analysis is disputed by the efficient-market hypothesis, which states that stock market prices are essentially unpredictable, and research on whether technical analysis offers any benefit has produced mixed results.
Comment (computer programming)In computer programming, a comment is a programmer-readable explanation or annotation in the source code of a computer program. They are added with the purpose of making the source code easier for humans to understand, and are generally ignored by compilers and interpreters. The syntax of comments in various programming languages varies considerably. Comments are sometimes also processed in various ways to generate documentation external to the source code itself by documentation generators, or used for integration with source code management systems and other kinds of external programming tools.
Ensemble learningIn statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms alone. Unlike a statistical ensemble in statistical mechanics, which is usually infinite, a machine learning ensemble consists of only a concrete finite set of alternative models, but typically allows for much more flexible structure to exist among those alternatives.
Comparison of programming languages (syntax)This comparison of programming languages compares the features of language syntax (format) for over 50 computer programming languages. Programming language expressions can be broadly classified into four syntax structures: prefix notation Lisp (* (+ 2 3) (expt 4 5)) infix notation Fortran (2 + 3) * (4 ** 5) suffix, postfix, or Reverse Polish notation Forth 2 3 + 4 5 ** * math-like notation TUTOR (2 + 3)(45) $$ note implicit multiply operator When a programming languages has statements, they typically have conventions for: statement separators; statement terminators; and line continuation A statement separator demarcates the boundary between two separate statements.
