API Reference - Models
Regression
| Model | Alternate Names | Use Cases |
|---|---|---|
| LinearRegression | None | Price Prediction, Time To Level Up Prediction |
| NormalLinearRegression (Not Recommended) | None | Same As Above |
| SupportVectorRegression (May Need Further Refinement) | SVR | Same As Above |
| KNearestNeighboursRegressor | KNN-R | Same As Above |
Classification
| Model | Alternate Names | Use Cases |
|---|---|---|
| KNearestNeighboursClassifier | KNN-C | Item Recommendation, Similar Player Matchmaking |
| LogisticRegression | Perceptron | Purchase Likelihood Estimation, Player Confidence Prediction |
| SupportVectorMachine | SVM | Hacking Detection, Anomaly Detection |
| GaussianNaiveBayes | None | Player Behavior Categorization (e.g., Cautious Vs. Aggressive), Fast State Classification |
| MultinomialNaiveBayes | None | Inventory Action Prediction, Strategy Profiling Based on Item Usage |
| BernoulliNaiveBayes | None | Binary Action Prediction (e.g., Jump Or Not), Quick Decision Filters |
| ComplementNaiveBayes | None | Imbalanced Decision Prediction (e.g., Rare Choices, Niche Paths) |
| NeuralNetwork | Multi-Layer Perceptron | Decision-Making, Player Behaviour Prediction |
Clustering
| Model | Alternate Names | Use Cases |
|---|---|---|
| AffinityPropagation | None | Player Grouping |
| AgglomerativeHierarchical | None | Enemy Difficulty Generation |
| DensityBasedSpatialClusteringOfApplicationsWithNoise | DBSCAN | Density Grouping |
| MeanShift | None | Boss Spawn Location Search Based On Player Locations |
| ExpectationMaximization | EM | Hacking Detection, Anomaly Detection |
| KMeans | None | Maximizing Area-of-Effect Abilities, Predictive Target Grouping |
| KMedoids | None | Player Grouping Based On Player Locations With Leader Identification |
Deep Reinforcement Learning
| Model | Alternate Names | Use Cases |
|---|---|---|
| DeepQLearning | Deep Q Network | Self-Learning Fighting AIs, Self-Learning Parkouring AIs, Self-Driving Cars |
| DeepDoubleQLearningV1 | Double Deep Q Network (2010) | Same As Deep Q-Learning |
| DeepDoubleQLearningV2 | Double Deep Q Network (2015) | Same As Deep Q-Learning |
| DeepClippedDoubleQLearning | Clipped Double Deep Q Network | Same As Deep Q-Learning |
| DeepStateActionRewardStateAction | Deep SARSA | Same As Deep Q-Learning |
| DeepDoubleStateActionRewardStateActionV1 | Double Deep SARSA | Same As Deep Q-Learning |
| DeepDoubleStateActionRewardStateActionV2 | Double Deep SARSA | Same As Deep Q-Learning |
| DeepExpectedStateActionRewardStateAction | Deep Expected SARSA | Same As Deep Q-Learning |
| DeepDoubleExpectedStateActionRewardStateActionV1 | Double Deep Expected SARSA | Same As Deep Q-Learning |
| DeepDoubleExpectedStateActionRewardStateActionV2 | Double Deep Expected SARSA | Same As Deep Q-Learning |
| ActorCritic | AC | Same As Deep Q-Learning |
| AdvantageActorCritic | A2C | Same As Deep Q-Learning |
| REINFORCE | None | Same As Deep Q-Learning |
| MonteCarloControl (May Need Further Refinement) | None | Same As Deep Q-Learning |
| OffPolicyMonteCarloControl | None | Same As Deep Q-Learning |
| VanillaPolicyGradient | VPG | Same As Deep Q-Learning |
| ProximalPolicyOptimization | PPO | Same As Deep Q-Learning |
| ProximalPolicyOptimizationClip | PPO-Clip | Same As Deep Q-Learning |
| SoftActorCritic | SAC | Same As Deep Q-Learning |
| DeepDeterministicPolicyGradient | DDPG | Same As Deep Q-Learning |
| TwinDelayedDeepDeterministicPolicyGradient | TD3 | Same As Deep Q-Learning |
Generative
| Model | Alternate Names | Use Cases |
|---|---|---|
| GenerativeAdversarialNetwork | GAN | Building And Image Generation |
| ConditionalGenerativeAdversarialNetwork | CGAN | Same As GAN, But Can Assign Classes |
| WassersteinGenerativeAdversarialNetwork | WGAN | Same As GAN, But More Stable |
| ConditionalWassersteinGenerativeAdversarialNetwork | CWGAN | Combination Of Both CGAN And WGAN |