Big data analysis using machine learning for social scientists and criminologists /:
This book provides a detailed description of the entire study process concerning gathering and analysing big data and making observations to develop a crime-prediction model that utilizes its findings. It offers an in-depth discussion of several processes, including text mining, which extracts usefu...
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| Main Authors: | , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Newcastle upon Tyne :
Cambridge Scholars Publishing,
2019.
|
| Subjects: | |
| Online Access: | DE-862 DE-863 |
| Summary: | This book provides a detailed description of the entire study process concerning gathering and analysing big data and making observations to develop a crime-prediction model that utilizes its findings. It offers an in-depth discussion of several processes, including text mining, which extracts useful information from online documents; opinion mining, which analyses the emotions contained in documents; machine learning for crime prediction; and visualization analysis. To accurately predict crimes using machine learning, it is necessary to procure high-quality training data. Machine learning com. |
| Physical Description: | 1 online resource |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9781527536791 1527536793 |
Staff View
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| 245 | 1 | 0 | |a Big data analysis using machine learning for social scientists and criminologists / |c by Juyong Song and Tae Min Song. |
| 264 | 1 | |a Newcastle upon Tyne : |b Cambridge Scholars Publishing, |c 2019. | |
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| 504 | |a Includes bibliographical references and index. | ||
| 520 | |a This book provides a detailed description of the entire study process concerning gathering and analysing big data and making observations to develop a crime-prediction model that utilizes its findings. It offers an in-depth discussion of several processes, including text mining, which extracts useful information from online documents; opinion mining, which analyses the emotions contained in documents; machine learning for crime prediction; and visualization analysis. To accurately predict crimes using machine learning, it is necessary to procure high-quality training data. Machine learning com. | ||
| 588 | 0 | |a Online resource; title from digital title page (viewed on August 13, 2019). | |
| 505 | 0 | |a Intro -- Table of Contents -- Installation and Use of R -- Installation of R -- Use of R -- Scientific Research Design -- Research Concepts -- Variable Measurement -- Unit of Analysis -- Sampling and Hypothesis Testing -- Statistical Analysis -- Overview of Machine Learning -- Introduction -- Machine Learning Training Data -- Development of a Cyber bullying Prediction Model Based on Machine Learning -- Naïve Bayes Classification Model -- Logistic Regression Model -- Random Forest Model -- Decision Tree Model -- Neural Network Model -- Support Vector Machine Model -- Association Analysis -- Cluster Analysis and Segmentation -- Machine Learning Model Evaluation -- Machine Learning Model Evaluation Using Misclassification Tables -- Machine Learning Model Evaluation Using ROC Curves -- Artificial Intelligence -- Calculate the Effect of Input Variables on Output Variables (Prediction Probability) -- Using Training Data with Input Variables to Create Dependent Variables -- Creating Data with the Same Training-Data and Predicted-Data Classifications -- Evaluating Existing Training Data and High Quality Training Data -- Creating an Artificial Intelligence with Machine Learning -- Visualization -- Visualization of Text Data -- Visualization of Time Series Data -- Visualization of Geographical Data -- Developing Machine Learning-Based Predictive Models of Adverse Drug Responses -- Introduction -- Research Subjects and Analysis Method -- Result -- Discussion and Conclusion -- Index. | |
| 650 | 0 | |a Data mining |x Industrial applications. | |
| 650 | 0 | |a Big data. |0 http://id.loc.gov/authorities/subjects/sh2012003227 | |
| 650 | 0 | |a Machine learning. |0 http://id.loc.gov/authorities/subjects/sh85079324 | |
| 650 | 0 | |a Crime |x Data processing. | |
| 650 | 0 | |a Electronic data processing. |0 http://id.loc.gov/authorities/subjects/sh85042288 | |
| 650 | 0 | |a Criminologists |x Data processing. | |
| 650 | 0 | |a Social scientists |x Data processing. | |
| 650 | 6 | |a Exploration de données (Informatique) |x Applications industrielles. | |
| 650 | 6 | |a Données volumineuses. | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 6 | |a Criminologistes |x Informatique. | |
| 650 | 6 | |a Spécialistes des sciences sociales |x Informatique. | |
| 650 | 7 | |a Machine learning |2 fast | |
| 650 | 7 | |a Crime |x Data processing |2 fast | |
| 650 | 7 | |a Big data |2 fast | |
| 650 | 7 | |a Electronic data processing |2 fast | |
| 655 | 4 | |a Libros electrónicos. | |
| 700 | 1 | |a Song, T'ae-min, |e author. | |
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| author | Song, Juyoung Song, T'ae-min |
| author_facet | Song, Juyoung Song, T'ae-min |
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| contents | Intro -- Table of Contents -- Installation and Use of R -- Installation of R -- Use of R -- Scientific Research Design -- Research Concepts -- Variable Measurement -- Unit of Analysis -- Sampling and Hypothesis Testing -- Statistical Analysis -- Overview of Machine Learning -- Introduction -- Machine Learning Training Data -- Development of a Cyber bullying Prediction Model Based on Machine Learning -- Naïve Bayes Classification Model -- Logistic Regression Model -- Random Forest Model -- Decision Tree Model -- Neural Network Model -- Support Vector Machine Model -- Association Analysis -- Cluster Analysis and Segmentation -- Machine Learning Model Evaluation -- Machine Learning Model Evaluation Using Misclassification Tables -- Machine Learning Model Evaluation Using ROC Curves -- Artificial Intelligence -- Calculate the Effect of Input Variables on Output Variables (Prediction Probability) -- Using Training Data with Input Variables to Create Dependent Variables -- Creating Data with the Same Training-Data and Predicted-Data Classifications -- Evaluating Existing Training Data and High Quality Training Data -- Creating an Artificial Intelligence with Machine Learning -- Visualization -- Visualization of Text Data -- Visualization of Time Series Data -- Visualization of Geographical Data -- Developing Machine Learning-Based Predictive Models of Adverse Drug Responses -- Introduction -- Research Subjects and Analysis Method -- Result -- Discussion and Conclusion -- Index. |
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| spelling | Song, Juyoung, author. Big data analysis using machine learning for social scientists and criminologists / by Juyong Song and Tae Min Song. Newcastle upon Tyne : Cambridge Scholars Publishing, 2019. ©2019 1 online resource text txt rdacontent computer c rdamedia online resource cr rdacarrier Includes bibliographical references and index. This book provides a detailed description of the entire study process concerning gathering and analysing big data and making observations to develop a crime-prediction model that utilizes its findings. It offers an in-depth discussion of several processes, including text mining, which extracts useful information from online documents; opinion mining, which analyses the emotions contained in documents; machine learning for crime prediction; and visualization analysis. To accurately predict crimes using machine learning, it is necessary to procure high-quality training data. Machine learning com. Online resource; title from digital title page (viewed on August 13, 2019). Intro -- Table of Contents -- Installation and Use of R -- Installation of R -- Use of R -- Scientific Research Design -- Research Concepts -- Variable Measurement -- Unit of Analysis -- Sampling and Hypothesis Testing -- Statistical Analysis -- Overview of Machine Learning -- Introduction -- Machine Learning Training Data -- Development of a Cyber bullying Prediction Model Based on Machine Learning -- Naïve Bayes Classification Model -- Logistic Regression Model -- Random Forest Model -- Decision Tree Model -- Neural Network Model -- Support Vector Machine Model -- Association Analysis -- Cluster Analysis and Segmentation -- Machine Learning Model Evaluation -- Machine Learning Model Evaluation Using Misclassification Tables -- Machine Learning Model Evaluation Using ROC Curves -- Artificial Intelligence -- Calculate the Effect of Input Variables on Output Variables (Prediction Probability) -- Using Training Data with Input Variables to Create Dependent Variables -- Creating Data with the Same Training-Data and Predicted-Data Classifications -- Evaluating Existing Training Data and High Quality Training Data -- Creating an Artificial Intelligence with Machine Learning -- Visualization -- Visualization of Text Data -- Visualization of Time Series Data -- Visualization of Geographical Data -- Developing Machine Learning-Based Predictive Models of Adverse Drug Responses -- Introduction -- Research Subjects and Analysis Method -- Result -- Discussion and Conclusion -- Index. Data mining Industrial applications. Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Crime Data processing. Electronic data processing. http://id.loc.gov/authorities/subjects/sh85042288 Criminologists Data processing. Social scientists Data processing. Exploration de données (Informatique) Applications industrielles. Données volumineuses. Apprentissage automatique. Criminologistes Informatique. Spécialistes des sciences sociales Informatique. Machine learning fast Crime Data processing fast Big data fast Electronic data processing fast Libros electrónicos. Song, T'ae-min, author. has work: Big data analysis using machine learning for social scientists and criminologists (Text) https://id.oclc.org/worldcat/entity/E39PCGJJckGYFwyXGqh7X9yxfy https://id.oclc.org/worldcat/ontology/hasWork Print version: Song, Juyoung. Big Data Analysis Using Machine Learning for Social Scientists and Criminologists. Newcastle upon Tyne : Cambridge Scholars Publishing, 2019 1527533883 9781527533882 (OCoLC)1100601153 |
| spellingShingle | Song, Juyoung Song, T'ae-min Big data analysis using machine learning for social scientists and criminologists / Intro -- Table of Contents -- Installation and Use of R -- Installation of R -- Use of R -- Scientific Research Design -- Research Concepts -- Variable Measurement -- Unit of Analysis -- Sampling and Hypothesis Testing -- Statistical Analysis -- Overview of Machine Learning -- Introduction -- Machine Learning Training Data -- Development of a Cyber bullying Prediction Model Based on Machine Learning -- Naïve Bayes Classification Model -- Logistic Regression Model -- Random Forest Model -- Decision Tree Model -- Neural Network Model -- Support Vector Machine Model -- Association Analysis -- Cluster Analysis and Segmentation -- Machine Learning Model Evaluation -- Machine Learning Model Evaluation Using Misclassification Tables -- Machine Learning Model Evaluation Using ROC Curves -- Artificial Intelligence -- Calculate the Effect of Input Variables on Output Variables (Prediction Probability) -- Using Training Data with Input Variables to Create Dependent Variables -- Creating Data with the Same Training-Data and Predicted-Data Classifications -- Evaluating Existing Training Data and High Quality Training Data -- Creating an Artificial Intelligence with Machine Learning -- Visualization -- Visualization of Text Data -- Visualization of Time Series Data -- Visualization of Geographical Data -- Developing Machine Learning-Based Predictive Models of Adverse Drug Responses -- Introduction -- Research Subjects and Analysis Method -- Result -- Discussion and Conclusion -- Index. Data mining Industrial applications. Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Crime Data processing. Electronic data processing. http://id.loc.gov/authorities/subjects/sh85042288 Criminologists Data processing. Social scientists Data processing. Exploration de données (Informatique) Applications industrielles. Données volumineuses. Apprentissage automatique. Criminologistes Informatique. Spécialistes des sciences sociales Informatique. Machine learning fast Crime Data processing fast Big data fast Electronic data processing fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh2012003227 http://id.loc.gov/authorities/subjects/sh85079324 http://id.loc.gov/authorities/subjects/sh85042288 |
| title | Big data analysis using machine learning for social scientists and criminologists / |
| title_auth | Big data analysis using machine learning for social scientists and criminologists / |
| title_exact_search | Big data analysis using machine learning for social scientists and criminologists / |
| title_full | Big data analysis using machine learning for social scientists and criminologists / by Juyong Song and Tae Min Song. |
| title_fullStr | Big data analysis using machine learning for social scientists and criminologists / by Juyong Song and Tae Min Song. |
| title_full_unstemmed | Big data analysis using machine learning for social scientists and criminologists / by Juyong Song and Tae Min Song. |
| title_short | Big data analysis using machine learning for social scientists and criminologists / |
| title_sort | big data analysis using machine learning for social scientists and criminologists |
| topic | Data mining Industrial applications. Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Crime Data processing. Electronic data processing. http://id.loc.gov/authorities/subjects/sh85042288 Criminologists Data processing. Social scientists Data processing. Exploration de données (Informatique) Applications industrielles. Données volumineuses. Apprentissage automatique. Criminologistes Informatique. Spécialistes des sciences sociales Informatique. Machine learning fast Crime Data processing fast Big data fast Electronic data processing fast |
| topic_facet | Data mining Industrial applications. Big data. Machine learning. Crime Data processing. Electronic data processing. Criminologists Data processing. Social scientists Data processing. Exploration de données (Informatique) Applications industrielles. Données volumineuses. Apprentissage automatique. Criminologistes Informatique. Spécialistes des sciences sociales Informatique. Machine learning Crime Data processing Big data Electronic data processing Libros electrónicos. |
| work_keys_str_mv | AT songjuyoung bigdataanalysisusingmachinelearningforsocialscientistsandcriminologists AT songtaemin bigdataanalysisusingmachinelearningforsocialscientistsandcriminologists |