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Game Data Science Using R
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Getting Started
Why Game Data Science?
Introduction to Game Data Science
Game Analytics
What is Game Data?
Historical Context for Game Data Science
Era of Game Data and Machine Learning
The Process of Game Data Science
What are Metrics in Game Data Science?
Introduction to Customer Metrics
Introduction to Gameplay Metrics
Key Performance Indicators
Importance of Metrics to Game Data Science
Summary: Basics of Game Data Science
Quiz on Basics of Game Data Science
Data Preprocessing
About This Chapter
What is Data Preprocessing?
Data Example and Measurement Types
Process for Preprocessing
Reading and Parsing Files
Purpose of Cleaning and Data Type Checks
Data Consistency Processing
Data Normalization and Standardization
Summary: Data reprocessing
Quiz on Preprocessing of Data
Introduction to Statistics and Probability Theory
Introduction to Probability and Statistics
Measures of Centrality
Measure of Spread
Introduction to Correlation Analysis
Introduction to Inferential Statistics
T-tests and its Types
Introduction to Analysis of Variance (ANOVA)
Introduction to Probability
Summary: Statistics and Probability Theory
Quiz on Statistics and Probability Theory
Data Abstraction
Significance of Behavioral Telemetry
Introduction to Dataset
Introduction to Feature Extraction
How to Deal with Nominal and Ordinal Measures?
The Process of Feature Selection
Introduction to Entropy
Summary: Data Abstraction
Quiz on Data Abstraction
Data Analysis through Visualization
Overview of the Chapter
Introduction to Heatmaps
Spatio-Temporal Visualization Systems
Exploring Spatio-Temporal Player Behavior in Dota 2
State-action Visualization Systems
Using State-action Transition to Compare Players’ Choices
Exploring Players' Dialogue Choices (Lab)
Summary: Data Analysis Through Visualization
Quiz on Data Analysis Through Visualization
Clustering Methods in Game Data Science
Introduction to Clusters
What is Cluster Analysis?
Clustering Models
The Clustering Process
Challenges in Applying the Clustering Process
Evaluating and Tuning the Results
Introduction to The K-means Algorithm
An Example of K-Means From the Wild: Tera Online
The k-Means lab
Introduction to Fuzzy C-Means
Fuzzy C-Means Lab
Basics of DBSCAN
DBSCAN Lab
Introduction to Hierarchical Clustering Methods
Hierarchical Clustering Lab
Introduction to Archetypal Analysis (AA)
Archetypal Analysis Lab
Introduction to Model-based Clustering
Advice on Applying Cluster Methods
Summary: Clustering Methods in Game Data Science
Quiz on Clustering Methods
Supervised Learning in Game Data Science
Introduction to Machine learning
Supervised Machine Learning
Ways to Categorize Prediction Models
Introduction to Regression Methods
Linear Regression Lab
Introduction to Classification
K-nearest-Neighbour(KNN) Lab
Introduction to Naive Bayes Theorem
Naive Bayes Lab
Introduction to Logistics Regression
Logistic Regression Lab
Introduction to Linear Discriminant Analysis (LDA)
Linear Discriminant Analysis (LDA) Lab
Introduction to Support Vector Machines (SVMs)
Support Vector Machine Lab
Kernel Methods with Support Vector Machines
Lab of Support Vector Machines with Kernel Methods
Introduction to Decision Trees
Decision Tree Lab
Introduction to Random Forests
Random Forests Lab
Summary: Supervised Learning in Game Data Science
Quiz on Supervised Learning
Model Validation and Evaluation
Introduction to Machine Learning Pipeline
How to Determine if the Model Is Good or Bad
Lab of Confusion Matrix
Introduction to Area Under the Curve (AUC)
Introduction to Regression Metrics
Regression Metrics Lab
What is Model Validation Process?
Cross-Validation Lab
How to Debug a Model That Is Already Trained
Summary: Model Validation and Evaluation
Quiz on Model Validation and Evaluation
Introduction to Neural Networks
What are Neural Networks?
What is a Feedforward Neural Network?
Working of a Feedforward Neural Network
How to Train Feedforward Neural Networks
Usage of Deep Neural Networks in Game Data Science
Introduction to Convolutional Neural Network
How Does the Convolutional Layer Work?
Usage of CNNs in Game Data Science
Summary: Neural Networks
Quiz on the Neural Networks
Sequence Analysis of Game Data
Introduction to Sequence Analysis
Why Sequence Data Analysis?
Sequence Mining Enables Player Profiling: A Case Study
Dota 2 Data
Exploratory Sequence Data Analysis
Inspecting Frequent Patterns in Explorative Analysis
The Entropy of States in Explorative Analysis
Lab of Exploratory Sequence Data Analysis
Introduction to Sequence Pattern Mining
Lab for SPADE
Introduction to Clustering of Sequences
Lab of Clustering Sequences
Summary: Sequence Analysis of Game Data
Quiz on Sequence Analysis of Game Data
Advanced Sequence Analysis
Introduction to Advanced Sequence Analysis
Probabilistic Planning-Based Approach
Introduction to PHATT planning approach
Introduction to Bayesian Networks
What are Hidden Markov Models (HMMs)?
Introduction to Markov Decision Process (MDP)
Usage of the Markov Decision Process in Games
Extension of Markov Decision Process
Introduction to Markov Logic Networks (MLNs)
Introduction to Recurrent Neural Networks (RNNs)
Usage of Recurrent Neural Networks (RNNs) in Games
Summary: Advanced Sequence Data Analysis
Quiz: Advanced Sequence Analysis
Case Study: Tom Clancy's The Division (TCTD)
Introduction to the Case Study
Game: Tom Clancy’s The Division (TCTD)
Data Analysis in the Case Study
Results of the Case Study
Discussion and Conclusion of the Case Study
Conclusion and Remarks
Game Data Science Process
Other Topics in Game Data Science
Copyright Information
Appendix A: Game Used in the Book
VPAL Game
How to Determine if the Model Is Good or Bad
Determine when a model is considered good or bad.
We'll cover the following
Performance metrics
Classification metrics
Confusion matrix
Explanation of confusion matrix
Recall in the confusion matrix
Specificty
Accuracy
Precision
F-measure
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