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Steps in reasoning
Inferences are steps in logical reasoning, moving from premises to logical consequences. Inference is traditionally divided into deduction and induction
Inference
Method of deriving conclusions
Rules of inference are ways of deriving conclusions from premises. They are integral parts of formal logic, serving as the logical structure of valid
Rule_of_inference
Process of using data analysis for predicting population data from sample data
Statistical inference is the process of using data analysis to infer properties of an underlying probability distribution. Inferential statistical analysis
Statistical_inference
Study of correct reasoning
formal and informal logic. Formal logic is the study of deductively valid inferences or logical truths. It examines how conclusions follow from premises based
Logic
Method of statistical inference
Bayesian inference (/ˈbeɪziən/ BAY-zee-ən or /ˈbeɪʒən/ BAY-zhən) is a method of statistical inference in which Bayes' theorem is used to calculate a probability
Bayesian_inference
Automatic detection of the type of an expression in a formal language
Type inference, sometimes called type reconstruction, refers to the automatic detection of the type of an expression in a formal language. These include
Type_inference
Branch of statistics
system. The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable
Causal_inference
Principle of common law
Adverse inference is a legal inference, adverse to the concerned party, drawn from silence or absence of requested evidence. It is part of evidence codes
Adverse_inference
Execution of machine learning models on edge devices
Edge inference is the process of running machine learning or deep learning models on local devices (edge devices) such as smartphones, IoT devices, embedded
Edge_inference
Hypothesis in neuroscience
Bayesian inference with active inference, where actions are guided by predictions and sensory feedback refines them. From it, wide-ranging inferences have
Free_energy_principle
Component of artificial intelligence systems
In the field of artificial intelligence, an inference engine is a software component of an intelligent system that applies logical rules to the knowledge
Inference_engine
Form of reasoning
Deductive reasoning is the process of drawing valid inferences. An inference is valid if its conclusion follows logically from its premises, meaning that
Deductive_reasoning
In mathematical logic, deep inference names a general idea in structural proof theory that breaks with the classical sequent calculus by generalising
Deep_inference
Method for estimating the parameters of economic models
Indirect inference is a simulation-based method for estimating the parameters of economic models. It is a computational method for determining acceptable
Indirect_inference
Approximate inference methods make it possible to learn realistic models from big data by trading off computation time for accuracy, when exact learning
Approximate_inference
Method of logical reasoning
prediction, statistical syllogism, argument from analogy, and causal inference. There are also differences in how their results are regarded. A generalization
Inductive_reasoning
Inference seeking the simplest and most likely explanation
Abductive reasoning (also called abduction, abductive inference, or retroduction) is a form of logical inference that seeks the simplest and most likely conclusion
Abductive_reasoning
Type of statistical inference
Frequentist inference is a type of statistical inference based in frequentist probability, which treats "probability" in equivalent terms to "frequency"
Frequentist_inference
Data mining technique
An inference attack is a data mining technique performed by analyzing data in order to illegitimately gain knowledge about a subject or database. A subject's
Inference_attack
Treatment for OCD
Inference-based therapy (IBT), also known as inference-based cognitive behavioral therapy (I-CBT), originated as a form of cognitive therapy developed
Inference-based_therapy
One of a number of different types of statistical inference
Fiducial inference is one of a number of different types of statistical inference. These are rules, intended for general application, by which conclusions
Fiducial_inference
Involuntary aspect of visual perception
In perceptual psychology, unconscious inference (German: unbewusster Schluss), also referred to as unconscious conclusion, is a term coined in 1867 by
Unconscious_inference
Philosophy of science concept emphasizing the need for alternative hypotheses
In philosophy of science, strong inference is a model of scientific inquiry that emphasizes the need for alternative hypotheses, rather than a single
Strong_inference
American semiconductor company
applications such as inference engines. Products include its wafer scale engine (WSE)-3 semiconductors, its CS-3 supercomputers, and its "AI inference cloud" and
Cerebras_Systems
Computational technique
Trajectory inference or pseudotemporal ordering is a computational technique used in single-cell transcriptomics to determine the pattern of a dynamic
Trajectory_inference
Aspect of cognitive therapy
Arbitrary inference is a classic tenet of cognitive therapy created by Aaron T. Beck in 1979. He defines the act of making an arbitrary inference as the
Arbitrary_inference
Software library for LLM inference
llama.cpp is an open-source software library that performs inference on various large language models such as Llama. It is co-developed alongside the
Llama.cpp
Spontaneous trait inference is the term utilised in social psychology to describe the mechanism that causes individuals to form impressions of people
Spontaneous_trait_inference
Open-source software for large language model inference
vLLM is an open-source software framework for inference and serving of large language models and related multimodal models. Originally developed at the
VLLM
Theory and paradigm of statistics
the event or conditions related to the event. For example, in Bayesian inference, Bayes' theorem can be used to estimate the parameters of a probability
Bayesian_statistics
Logical inference from a single statement
An immediate inference is an inference which can be made from only one statement or proposition. For instance, from the statement "All toads are green"
Immediate_inference
Method of forming inferences
reasoning) is an inference method described colloquially as working backward from the goal. It is used in automated theorem provers, inference engines, proof
Backward_chaining
Artificial intelligence software company
Inference Corporation was an American software company that specialized in artificial intelligence systems. Los Angeles-based Inference was founded in
Inference_Corporation
Mathematical rule for inverting probabilities
of Bayes' theorem's many applications is Bayesian inference, an approach to statistical inference, where it is used to invert the probability of observations
Bayes'_theorem
Process of logical induction or deduction during reading
Text inferencing describes the tacit or active process of logical induction or deduction during reading. Inferences are used to bridge current text ideas
Text_inferencing
Formal fallacy in statistical interpretation
ecological inference fallacy or population fallacy) is a formal fallacy in the interpretation of statistical data that occurs when inferences about the
Ecological_fallacy
Statistical interpretation with many tests
rate (FWER). The larger the number of inferences made in a series of tests, the more likely erroneous inferences become. Several statistical techniques
Multiple_comparisons_problem
Probabilistic graphical representation of causal relationships
of the presence of various diseases. Efficient algorithms can perform inference and learning in Bayesian networks. Bayesian networks that model sequences
Bayesian_network
Intelligent design book by William A. Dembski and Winston Ewert
The Design Inference: Eliminating Chance through Small Probabilities is a book which sets out to establish approaches by which evidence of intelligent
The_Design_Inference
Range to estimate an unknown parameter
According to frequentist inference, a confidence interval (CI) is a range of values which is likely to contain (in repeated sampling) the true value of
Confidence_interval
Type of artificial neural network
An adaptive neuro-fuzzy inference system or adaptive network-based fuzzy inference system (ANFIS) is a kind of artificial neural network that is based
Adaptive neuro fuzzy inference system
Adaptive_neuro_fuzzy_inference_system
Phenomenon in natural language
games. You can watch a movie or you can play video games. Free choice inferences are a major topic of research in formal semantics and philosophical logic
Free_choice_inference
of inference is an archaeological argument outlined by Christopher Hawkes in a 1954 paper that describes increasing difficulty of making inferences about
Hawkes'_ladder_of_inference
Misuse of data analysis
correction, more sophisticated selective inference methods are available. The most common selective inference method is the use of Benjamini and Hochberg's
Data_dredging
Method of statistical analysis
dilemma is the "fundamental problem of causal inference." Because of the fundamental problem of causal inference, unit-level causal effects cannot be directly
Rubin_causal_model
Inference engine in an expert system
reasoning) is one of the two main methods of reasoning when using an inference engine and can be described logically as repeated application of modus
Forward_chaining
System for reasoning about vagueness
usually used within other complex methods, such as in adaptive neuro fuzzy inference systems. Since the fuzzy system output is a consensus of all of the inputs
Fuzzy_logic
2000 book by Judea Pearl
Causality: Models, Reasoning, and Inference (2000; updated 2009) is a book by Judea Pearl. It is an exposition and analysis of causality. It is considered
Causality_(book)
Intelligence of machines
decision support, knowledge discovery (mining "interesting" and actionable inferences from large databases), and other areas. A knowledge base is a body of
Artificial_intelligence
Evidence indirectly supporting conclusion
Circumstantial evidence is evidence that relies on an inference to connect it to a conclusion of fact, such as a fingerprint at the scene of a crime.
Circumstantial_evidence
This is a list of rules of inference, logical laws that relate to mathematical formulae. Rules of inference are syntactical transform rules which one can
List_of_rules_of_inference
2011 Japanese novel by Kyo Shirodaira and its adaptations
In/Spectre (Japanese: 虚構推理, Hepburn: Kyokō Suiri), also known as Invented Inference in Japan, is a 2011 Japanese novel published by Kodansha and written by
In/Spectre
Process in logic
In logic, inference is the process of deriving logical conclusions from premises known or assumed to be true. In checking a logical inference for formal
Material_inference
Type of statistical analysis
Nonparametric statistics can be used for descriptive statistics or statistical inference. Nonparametric tests are often used when the assumptions of parametric
Nonparametric_statistics
Statistical method for molecular phylogenetics
Bayesian inference of phylogeny combines the information in the prior and in the data likelihood to create the so-called posterior probability of trees
Bayesian inference in phylogeny
Bayesian_inference_in_phylogeny
Mathematical methods used in Bayesian inference and machine learning
techniques for approximating intractable integrals arising in Bayesian inference and machine learning. They are typically used in complex statistical models
Variational_Bayesian_methods
Type of inference
Biological network inference is the process of making inferences and predictions about biological networks. By using these networks to analyze patterns
Biological_network_inference
Type of machine learning model
open-source C/C++ large language model inference framework for local and cross-platform deployment SGLang – open-source inference engine and framework for large
Large_language_model
Language models designed for reasoning tasks
revise earlier reasoning steps and utilize additional computation during inference as a method to scale performance, complementing traditional scaling approaches
Reasoning_model
Study of collection and analysis of data
experiment designs and survey samples. Representative sampling assures that inferences and conclusions can reasonably extend from the sample to the population
Statistics
System of formal deduction in logic
system that generates theorems from axioms and inference rules, especially if the only postulated inference rule is modus ponens. Every Hilbert system is
Hilbert_system
Interpretation of probability
a probability is assigned to a hypothesis, whereas under frequentist inference, a hypothesis is typically tested without being assigned a probability
Bayesian_probability
Method of estimating the parameters of a statistical model, given observations
flexible, and as such the method has become a dominant means of statistical inference. If the likelihood function is differentiable, the derivative test for
Maximum_likelihood_estimation
Number measuring the chance an event occurs
computer science, game theory, and philosophy to, for example, draw inferences about the expected frequency of events. Probability theory is also used
Probability
Study of consumption of goods and services
Consumer behaviour is the study of individuals, groups, or organisations and all activities associated with the purchase, use and disposal of goods and
Consumer_behaviour
Machine-learning process
Grammar induction (or grammatical inference) is the process in machine learning of learning a formal grammar (usually as a collection of re-write rules
Grammar_induction
Software able to infer logical consequences
reasoner generalizes that of an inference engine, by providing a richer set of mechanisms to work with. The inference rules are commonly specified by
Semantic_reasoner
Information conveyed verbally yet not literally
many other researchers. Entailment, or implication, in logic Free choice inference Indirect speech act Presupposition Davis (2019, section 14) Grice (1975:24–26)
Implicature
Computational method in Bayesian statistics
posterior distributions of model parameters. In all model-based statistical inference, the likelihood function is of central importance, since it expresses
Approximate Bayesian computation
Approximate_Bayesian_computation
Mistaking an imagined possibility for a real probability
causes the individual to overestimate the threat. Inverse inference, the inverse of normal inference, is a critical concept of inferential confusion. A person
Inferential_confusion
Question of whether inductive reasoning leads to definitive knowledge
based on previous observations. These inferences from the observed to the unobserved are known as "inductive inferences". David Hume, who first formulated
Problem_of_induction
Memory allocation scheme
regions for safe memory allocation by introducing the concept of region inference, where the creation and deallocation of regions, as well as the assignment
Region-based memory management
Region-based_memory_management
Philosophical problem-solving principle
known entities for inferences to unknown entities." Around 1960, Ray Solomonoff founded the theory of universal inductive inference, the theory of prediction
Occam's_razor
Type system used in computer programming and mathematics
programmer-supplied type annotations or other hints. Algorithm W is an efficient type inference method in practice and has been successfully applied on large code bases
Hindley–Milner_type_system
Monograph
Geometric and Topological Inference is a monograph in computational geometry, computational topology, geometry processing, and topological data analysis
Geometric and Topological Inference
Geometric_and_Topological_Inference
Mathematical theory
Solomonoff's theory of inductive inference purportedly proves that, under its assumptions (axioms), the best possible scientific model is the shortest
Solomonoff's theory of inductive inference
Solomonoff's_theory_of_inductive_inference
Process of drawing correct inferences
to arrive at a conclusion in a rigorous way. It happens in the form of inferences or arguments by starting from a set of premises and reasoning to a conclusion
Logical_reasoning
Theory and paradigm of statistics
of statistical inference, while others make inferences based on likelihood, but without using Bayesian inference or frequentist inference. Likelihoodism
Likelihoodist_statistics
Bearer of truth values
concrete content, often expressed through rules of inference. For example, modus ponens is a rule of inference that links premises of the form "if P {\displaystyle
Proposition
Method of estimating the parameters of a statistical model
characterized by the use of distributions to summarize data and draw inferences: thus, Bayesian methods tend to report the posterior mean or median instead
Maximum a posteriori estimation
Maximum_a_posteriori_estimation
that researchers must take into account. One key assumption for unbiased inference is the non-interference assumption, which posits that an individual's
Spillover_(experiment)
Application of statistical methods to marketing processes
In marketing, Bayesian inference allows for decision making and market research evaluation under uncertainty and with limited data. The communication
Bayesian inference in marketing
Bayesian_inference_in_marketing
Open-source framework for large language model inference
with a runtime for high-throughput inference. The project is designed for low latency and high-throughput inference workloads, and its documentation describes
SGLang
Rewriting system and type of formal grammar
represents a significant advancement in L-system inference, introducing the Plant Model Inference Tools (PMIT) suite. Despite the name, this tool is
L-system
Canadian philosopher (1936–2023)
translated into several languages. His works include: Logic of Statistical Inference (1965) A Concise Introduction to Logic (1972) ISBN 978-0-394-31008-4 The
Ian_Hacking
Overview of and topical guide to logic
statements and arguments, both through the study of formal systems of inference and the study of arguments in natural language. The scope of logic can
Outline_of_logic
Study of the scope and nature of logic
literature. Logic is often seen as the study of correct reasoning, valid inference, or logical consequence. It is a formal science that investigates how
Philosophy_of_logic
Estimator for quality of a statistical model
statistical inference generally can be done within the AIC paradigm. The most commonly used paradigms for statistical inference are frequentist inference and
Akaike_information_criterion
Study of mental functions and behaviors
goal contagion: the adoption of goals, sometimes unconsciously, based on inferences about the goals of others. Vohs and Baumeister suggest that contrary to
Psychology
1994 book written by Gary King, Robert Keohane, and Sidney Verba
Designing Social Inquiry: Scientific Inference in Qualitative Research (or KKV) is an influential 1994 book written by Gary King, Robert Keohane, and
Designing_Social_Inquiry
Method of statistical inference
A statistical hypothesis test is a method of statistical inference used to decide whether the data provide sufficient evidence to reject a particular
Statistical_hypothesis_test
In constraint satisfaction, constraint inference is a relationship between constraints and their consequences. A set of constraints D {\displaystyle D}
Constraint_inference
Concept in natural language processing
language processing, textual entailment (TE), also known as natural language inference (NLI), is a directional relation between text fragments. The relation
Textual_entailment
Set of random variables
likelihood of a model requires inference in the model, which is generally computationally infeasible (see 'Inference' below). A multivariate normal distribution
Markov_random_field
Ontology infrastructure for the Semantic Web
OIL (Ontology Inference Layer or Ontology Interchange Language) can be regarded as an ontology infrastructure for the Semantic Web. OIL is based on concepts
Ontology_Inference_Layer
Study of general and fundamental questions
Often-discussed sources of knowledge are perception, introspection, memory, inference, and testimony. According to empiricists, all knowledge is based on some
Philosophy
Inference rules in database theory
Armstrong's axioms are a set of axioms (or, more precisely, inference rules) used to infer all the functional dependencies on a relational database. They
Armstrong's_axioms
Probability distribution
model for the random behavior of percentages and proportions. In Bayesian inference, the beta distribution is the conjugate prior probability distribution
Beta_distribution
Algorithmic inference gathers new developments in the statistical inference methods made feasible by the powerful computing devices widely available to
Algorithmic_inference
Theory in psychology
major domains of deductive inference, including relational inferences (spatial and temporal reasoning), propositional inferences (conditional, disjunctive
Mental model theory of reasoning
Mental_model_theory_of_reasoning
INFERENCE
INFERENCE
Girl/Female
Tamil
Inference
Girl/Female
Indian
Inference
INFERENCE
INFERENCE
Boy/Male
English
Free friend; noble friend.
Boy/Male
Indian
Gorgeous
Girl/Female
Irish
Beautiful. Dear child.
Boy/Male
Anglo Saxon English
Name of a king.
Girl/Female
Greek
Ethereal.
Female
Russian
(ЕвдокиÑ) Bulgarian and Russian form of Greek Eudokia, EVDOKIYA means "good-seeming."
Boy/Male
Hindu
Lord Shiva
Girl/Female
Hindu
Girl/Female
Australian, Finnish, French, German, Greek, Japanese, Swedish
Wise; Wisdom
Girl/Female
Arabic, Muslim
White
INFERENCE
INFERENCE
INFERENCE
INFERENCE
INFERENCE
adv.
From this reason; as an inference or deduction.
n.
A supposition; a proposition or principle which is supposed or taken for granted, in order to draw a conclusion or inference for proof of the point in question; something not proved, but assumed for the purpose of argument, or to account for a fact or an occurrence; as, the hypothesis that head winds detain an overdue steamer.
n.
Conclusion; inference.
n.
That which follows as the logical result of reasoning; inference; conclusion; suggestion.
a.
Following by logical sequence; reasonable; as, a legitimate result; a legitimate inference.
a.
Not forced; easy; natural; as, a unstrained deduction or inference.
a.
Characterized by, or addicted to, ratiocination; consisting in the comparison of propositions or facts, and the deduction of inferences from the comparison; argumentative; as, a ratiocinative process.
a.
According to the rules of logic; as, a logical argument or inference; the reasoning is logical.
adv.
By way of inference.
v. i.
That act of the mind by which two notions or ideas which are apprehended as distinct are compared for the purpose of ascertaining their agreement or disagreement. See 1. The comparison may be threefold: (1) Of individual objects forming a concept. (2) Of concepts giving what is technically called a judgment. (3) Of two judgments giving an inference. Judgments have been further classed as analytic, synthetic, and identical.
n.
An erroneous inference or conclusion.
adv.
In present circumstances; things being as they are; -- hence, used as a connective particle, to introduce an inference or an explanation.
n.
The act of immediate inference, by which we deny the opposite of anything which has been affirmed; as, all men are mortal; then, by obversion, no men are immortal. This is also described as "immediate inference by privative conception."
conj.
When in fact; while on the contrary; the case being in truth that; although; -- implying opposition to something that precedes; or implying recognition of facts, sometimes followed by a different statement, and sometimes by inferences or something consequent.
a.
Assumed without proof; as, a postulated inference.
a.
Not transgressing the requirement of truth and propriety; conformed to the truth of things, to reason, or to a proper standard; exact; normal; reasonable; regular; due; as, a just statement; a just inference.
n.
A keeping of the hearer in doubt and in attentive expectation of what is to follow, or of what is to be the inference or conclusion from the arguments or observations employed.
v. t. & i.
To infer from an inference already made.
a.
That premise which contains the major term. It its the first proposition of a regular syllogism; as: No unholy person is qualified for happiness in heaven [the major]. Every man in his natural state is unholy [minor]. Therefore, no man in his natural state is qualified for happiness in heaven [conclusion or inference].