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11 - Model ensembles
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7 - Linear models
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10 - Features
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Frontmatter
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5 - Tree models
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3 - Beyond binary classification
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2 - Binary classification and related tasks
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12 - Machine learning experiments
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Prologue: A machine learning sampler
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Contents
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Machine Learning
- The Art and Science of Algorithms that Make Sense of Data
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6 - Rule models
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9 - Probabilistic models
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Important points to remember
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Preface
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References
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8 - Distance-based models
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4 - Concept learning
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1 - The ingredients of machine learning
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10 - Does the Internet have an Achilles' heel?
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