HistoryHistory (derived ) is the systematic study and documentation of the human past. The period of events before the invention of writing systems is considered prehistory. "History" is an umbrella term comprising past events as well as the memory, discovery, collection, organization, presentation, and interpretation of these events. Historians seek knowledge of the past using historical sources such as written documents, oral accounts, art and material artifacts, and ecological markers.
Intellectual historyIntellectual history (also the history of ideas) is the study of the history of human thought and of intellectuals, people who conceptualize, discuss, write about, and concern themselves with ideas. The investigative premise of intellectual history is that ideas do not develop in isolation from the thinkers who conceptualize and apply those ideas; thus the intellectual historian studies ideas in two contexts: (i) as abstract propositions for critical application; and (ii) in concrete terms of culture, life, and history.
Counterfactual historyCounterfactual history (also virtual history) is a form of historiography that attempts to answer the What if? questions that arise from counterfactual conditions. As a method of intellectual enquiry, counterfactual history explores history and historical incidents by extrapolating a timeline in which key historical events either did not occur or had an outcome different from the actual historical outcome. Counterfactual history seeks by "conjecturing on what did not happen, or what might have happened, in order to understand what did happen.
Predictive analyticsPredictive analytics is a form of business analytics applying machine learning to generate a predictive model for certain business applications. As such, it encompasses a variety of statistical techniques from predictive modeling and machine learning that analyze current and historical facts to make predictions about future or otherwise unknown events. It represents a major subset of machine learning applications; in some contexts, it is synonymous with machine learning.
Predictive modellingPredictive modelling uses statistics to predict outcomes. Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. For example, predictive models are often used to detect crimes and identify suspects, after the crime has taken place. In many cases, the model is chosen on the basis of detection theory to try to guess the probability of an outcome given a set amount of input data, for example given an email determining how likely that it is spam.
Alternate historyAlternate history (also alternative history, allohistory, althist, or AH) is a subgenre of speculative fiction in which one or more historical events have occurred but are resolved differently than in actual history. As conjecture based upon historical fact, alternate history stories propose What if? scenarios about crucial events in human history, and present outcomes very different from the historical record. Some alternate histories are considered a subgenre of literary fiction, science fiction, or historical fiction.
PredictionA prediction (Latin præ-, "before," and dicere, "to say"), or forecast, is a statement about a future event or data. They are often, but not always, based upon experience or knowledge. There is no universal agreement about the exact difference from "estimation"; different authors and disciplines ascribe different connotations. Future events are necessarily uncertain, so guaranteed accurate information about the future is impossible. Prediction can be useful to assist in making plans about possible developments.
Decision-makingIn psychology, decision-making (also spelled decision making and decisionmaking) is regarded as the cognitive process resulting in the selection of a belief or a course of action among several possible alternative options. It could be either rational or irrational. The decision-making process is a reasoning process based on assumptions of values, preferences and beliefs of the decision-maker. Every decision-making process produces a final choice, which may or may not prompt action.
Decision theoryDecision theory (or the theory of choice; not to be confused with choice theory) is a branch of applied probability theory and analytic philosophy concerned with the theory of making decisions based on assigning probabilities to various factors and assigning numerical consequences to the outcome. There are three branches of decision theory: Normative decision theory: Concerned with the identification of optimal decisions, where optimality is often determined by considering an ideal decision-maker who is able to calculate with perfect accuracy and is in some sense fully rational.
Decision tree learningDecision tree learning is a supervised learning approach used in statistics, data mining and machine learning. In this formalism, a classification or regression decision tree is used as a predictive model to draw conclusions about a set of observations. Tree models where the target variable can take a discrete set of values are called classification trees; in these tree structures, leaves represent class labels and branches represent conjunctions of features that lead to those class labels.
Decision treeA decision tree is a decision support hierarchical model that uses a tree-like model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. It is one way to display an algorithm that only contains conditional control statements. Decision trees are commonly used in operations research, specifically in decision analysis, to help identify a strategy most likely to reach a goal, but are also a popular tool in machine learning.
Decision modelA decision model in decision theory is the starting point for a decision method within a formal (axiomatic) system. Decision models contain at least one action axiom. An action is in the form "IF is true, THEN do ". An action axiom tests a condition (antecedent) and, if the condition has been met, then (consequent) it suggests (mandates) an action: from knowledge to action. A decision model may also be a network of connected decisions, information and knowledge that represents a decision-making approach that can be used repeatedly (such as one developed using the Decision Model and Notation standard).
