Читать книгу Machine Learning Paradigm for Internet of Things Applications - Группа авторов - Страница 4

1 Chapter 2Table 2.1 Feasibility study summary.Table 2.2 Harvest prediction: Raw data fields.Table 2.3 Paddy harvest prediction - Data set.Table 2.4 Demand predict: Raw data fields.Table 2.5 Rice demand prediction: Data set.Table 2.6 Mutation rate effect.Table 2.7 Mutation probability effect.

2 Chapter 3Table 3.1 Classification accuracy.

3 Chapter 5Table 5.1 Text-based CAPTCHA used in commercial website.Table 5.2 Breaking methodology and success rate of various sources.Table 5.3 Pixel value changed entry.Table 5.4 Look up table entry.

4 Chapter 7Table 7.1 Offline evaluation metrics.Table 7.2 Illustration of confusion matrix.Table 7.3 Overview of additional metrics.Table 7.4 Overview of filtering techniques.Table 7.5 Overview of classifier algorithm.Table 7.6 Overview of the explored dataset.Table 7.7 System generated metric results using MovieLens with Random and SVD wh...Table 7.8 System generated metric results using MovieLens with SVD and SVD++ whe...

5 Chapter 8Table 8.1 Raspberry Pi history with version and configuration.

6 Chapter 9Table 9.1 Phase 2: algorithm for key hub identification.Table 9.2 Phase 3: algorithm for vehicle routing.

7 Chapter 13Table 13.1 Comparison of various routing protocols for different quality paramet...

8 Chapter 14Table 14.1 Dataset description.Table 14.2 Model metric parameters.