標(biāo)題: Titlebook: An Introduction to Artificial Psychology; Application Fuzzy Se Hojjatollah Farahani,Marija Blagojevi?,Sara Saljou Book 2023 The Editor(s) ( [打印本頁] 作者: 壓榨機(jī) 時間: 2025-3-21 18:32
書目名稱An Introduction to Artificial Psychology影響因子(影響力)
書目名稱An Introduction to Artificial Psychology影響因子(影響力)學(xué)科排名
書目名稱An Introduction to Artificial Psychology網(wǎng)絡(luò)公開度
書目名稱An Introduction to Artificial Psychology網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱An Introduction to Artificial Psychology被引頻次
書目名稱An Introduction to Artificial Psychology被引頻次學(xué)科排名
書目名稱An Introduction to Artificial Psychology年度引用
書目名稱An Introduction to Artificial Psychology年度引用學(xué)科排名
書目名稱An Introduction to Artificial Psychology讀者反饋
書目名稱An Introduction to Artificial Psychology讀者反饋學(xué)科排名
作者: 珊瑚 時間: 2025-3-21 22:02
,Markenführung als Managementprozess,ibutions used to illustrate the membership of these fuzzy sets of perceptions are defined and illustrated, such as cardinality, support, core, height, normalization, and crossover points. Finally, a worked example with code using procedures in R is given, looking at the relationship between depression and multiple sclerosis.作者: creatine-kinase 時間: 2025-3-22 00:40
https://doi.org/10.1007/978-3-8350-5438-7 data as genetic information based upon pairs of chromosomes. These models incorporate concepts in genetic models such as parents, children, reproduction, and mutation. An example of the use of this genetic approach to feature selection in machine learning is illustrated in R using two 10-item subscales from a questionnaire measuring sexual pain.作者: Arb853 時間: 2025-3-22 05:04
In Search of a Method, in the interpretation of the .-value and associated dangers, such as giving the impression that the world is “black and white,” and motivate the need for complementary more nuanced approaches to testing statistical hypotheses that can overcome these deficiencies.作者: restrain 時間: 2025-3-22 11:12
Fuzzy Set Theory and Psychology,ibutions used to illustrate the membership of these fuzzy sets of perceptions are defined and illustrated, such as cardinality, support, core, height, normalization, and crossover points. Finally, a worked example with code using procedures in R is given, looking at the relationship between depression and multiple sclerosis.作者: 使隔離 時間: 2025-3-22 14:58 作者: 有雜色 時間: 2025-3-22 18:40
codes which can be used on data from readers’ own fields of Artificial Psychology (AP) is a highly multidisciplinary field of study in psychology. AP tries to solve problems which occur when psychologists do research and need a robust analysis method. Conventional statistical approaches have deep ro作者: Epithelium 時間: 2025-3-22 21:59 作者: deceive 時間: 2025-3-23 01:43
https://doi.org/10.1007/978-3-663-01754-7tion from complex mental systems using ideas such as fuzziness of a system and unsupervised algorithms that use artificial intelligence. We discuss the need for a multiplicity of modeling approaches to help us to understand the world. We mention issues involving hypothesis testing; in particular, we作者: 缺乏 時間: 2025-3-23 05:57
,Markenführung als Managementprozess,cial psychology in model building. We recommend the use of a training set to estimate models and a separate set of data to test, in an unbiased manner, the predictive validity of the model obtained from the training set. This leads us to the increasingly popular techniques of machine learning and de作者: gait-cycle 時間: 2025-3-23 13:22 作者: Barter 時間: 2025-3-23 17:19 作者: 吝嗇性 時間: 2025-3-23 19:31
,Herausforderungen der Markenführung,onship between variables. Given the complexity of relationships between concepts, network models are multivariate and often highly dimensional, so there is often a need to reduce the number of variables using techniques such as exploratory factor analysis and LASSO, which uses a tuning parameter spe作者: 剛毅 時間: 2025-3-24 00:30
,Markenführung als Managementprozess, with a detailed description of the structure of neurons and artificial neurons that comprise these networks. A neural net is a conceptual model based upon the human brain. It has an observed input layer that connects to a middle, hidden layer consisting of an unobserved number of synapses and neuro作者: RODE 時間: 2025-3-24 02:22
https://doi.org/10.1007/978-3-8350-5438-7feature selection to narrow down characteristics of interest to create more parsimonious and cost-effective models. Aspects of feature selection such as choice of method (wrapper, embedded, and filter), evaluation functions used to identify an optimal subset of features, and validation of model fit 作者: Measured 時間: 2025-3-24 06:30 作者: 我沒有命令 時間: 2025-3-24 11:44 作者: peritonitis 時間: 2025-3-24 16:32 作者: BLAZE 時間: 2025-3-24 19:31
https://doi.org/10.1007/978-3-031-31172-7Cognitive Psychology; Cognitive Science; Machine learning; Artificial Intelligence; Fuzzy psychology; Psy作者: Trigger-Point 時間: 2025-3-25 01:11
978-3-031-31174-1The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: 簡略 時間: 2025-3-25 06:41
o explainthe set-oriented methodology and this book combines the precision of quantitative methods with information from qualitative methods. This is a book that many researchers can use to expand and deepen th978-3-031-31174-1978-3-031-31172-7作者: EXCEL 時間: 2025-3-25 07:38
Artificial Psychology,l should be parsimionious, easy to interpret, explainable, and understandable. We refer to three stages in the fitting of a model: the pre-model stage, the intrinsic stage, and the post-model interpretability stage and to different types of machine learning models.作者: Sarcoma 時間: 2025-3-25 13:28 作者: hysterectomy 時間: 2025-3-25 18:28
Network Analysis in AP,ns and regions in an individual’s brain is introduced together with the size of such systems (microscopic, macroscopic) and types of connectivity. Independent component analysis can look at changes in brain networks over time. A worked example fitting and using the aspects of networks discussed earl作者: 清洗 時間: 2025-3-25 22:33
Deep Neural Network,are error. Tips are given on how to Interpret these fit indices. The learning rate, epoch, and batch, which control the amount of learning input data used, are described. A worked example in R is at the end of the chapter looking at stress and anxiety levels in a child and its mother being used to p作者: Tidious 時間: 2025-3-26 03:15
Bayesian Inference and Models in AP, models are an extension of the classical logistic regression model to incorporate a priori information into classification. The use of cross-validation in unbiased model assessment is presented and illustrated via k-fold cross-validation, which splits the data into design and test sets. Finally, th作者: Evocative 時間: 2025-3-26 06:39
,Markenführung als Managementprozess,l should be parsimionious, easy to interpret, explainable, and understandable. We refer to three stages in the fitting of a model: the pre-model stage, the intrinsic stage, and the post-model interpretability stage and to different types of machine learning models.作者: acrophobia 時間: 2025-3-26 11:06 作者: 協(xié)迫 時間: 2025-3-26 14:07
,Herausforderungen der Markenführung,ns and regions in an individual’s brain is introduced together with the size of such systems (microscopic, macroscopic) and types of connectivity. Independent component analysis can look at changes in brain networks over time. A worked example fitting and using the aspects of networks discussed earl作者: sigmoid-colon 時間: 2025-3-26 17:58 作者: arcane 時間: 2025-3-26 23:46
https://doi.org/10.1007/978-3-8350-5438-7 models are an extension of the classical logistic regression model to incorporate a priori information into classification. The use of cross-validation in unbiased model assessment is presented and illustrated via k-fold cross-validation, which splits the data into design and test sets. Finally, th作者: ANTE 時間: 2025-3-27 01:15 作者: cartilage 時間: 2025-3-27 06:59
In Search of a Method,tion from complex mental systems using ideas such as fuzziness of a system and unsupervised algorithms that use artificial intelligence. We discuss the need for a multiplicity of modeling approaches to help us to understand the world. We mention issues involving hypothesis testing; in particular, we作者: Constant 時間: 2025-3-27 13:09
Artificial Psychology,cial psychology in model building. We recommend the use of a training set to estimate models and a separate set of data to test, in an unbiased manner, the predictive validity of the model obtained from the training set. This leads us to the increasingly popular techniques of machine learning and de作者: filicide 時間: 2025-3-27 17:11 作者: 急急忙忙 時間: 2025-3-27 19:37 作者: CRASS 時間: 2025-3-28 01:21 作者: 周年紀(jì)念日 時間: 2025-3-28 03:29
Deep Neural Network, with a detailed description of the structure of neurons and artificial neurons that comprise these networks. A neural net is a conceptual model based upon the human brain. It has an observed input layer that connects to a middle, hidden layer consisting of an unobserved number of synapses and neuro作者: 叫喊 時間: 2025-3-28 08:57
Feature Selection in AP,feature selection to narrow down characteristics of interest to create more parsimonious and cost-effective models. Aspects of feature selection such as choice of method (wrapper, embedded, and filter), evaluation functions used to identify an optimal subset of features, and validation of model fit 作者: ARCH 時間: 2025-3-28 12:33
Bayesian Inference and Models in AP,h as the probability of a patient having a severe memory impairment given their gender. We then compare this approach with classical Fisherian inference giving Bayesian analogs based on summarizing the posterior distributions of estimates using percentiles to give medians and credible regions. Other作者: Ebct207 時間: 2025-3-28 15:00
10樓作者: Palpitation 時間: 2025-3-28 20:47
10樓作者: 健壯 時間: 2025-3-29 02:51
10樓作者: Intrepid 時間: 2025-3-29 03:13
10樓
