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β€Žbook.toml

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[book]
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authors = ["matchy233"]
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language = "en"
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multilingual = false
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multilingual = true
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src = "src"
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title = "Notes @ ETH ZΓΌrich"
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[output.html]
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additional-js = ["mermaid.min.js", "mermaid-init.js"]
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mathjax-support = true
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default-theme = "Rust"
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preferred-dark-theme = "Ayu"
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additional-js = ["mermaid.min.js", "mermaid-init.js"]
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additional-css = ["theme/custom.css"]
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[output.html.fold]
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enable = true

β€Žsrc/22hs/dm1/02_classification.md

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# Classification Algorithms
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Here is a detailed summary of the **Classification Algorithms** in the uploaded document organized into bullet points and course notes. I have included key equations, concepts, and figures where possible.
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---
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## **Classification Overview**
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- **Problem**: Given an object \\(x\\), predict its class label \\(y\\). Examples include identifying objects in computer vision, detecting fraudulent credit card transactions, and gene classification in personalized medicine.

β€Žsrc/22hs/dm1/04_feature_selection.md

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# Feature Selection
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Here is a detailed summary and course notes for the uploaded document on **Feature Selection** from **Data Mining**:
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---
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## **What is Feature Selection?**
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- **Definition**: Feature selection involves identifying a relevant subset of features \\( X \\) that are most predictive of the output variable \\( Y \\) in supervised learning tasks.

β€Žsrc/22hs/dm1/05_applications_in_computational_biology.md

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# Applications in Computational Biology
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Here is a detailed summary and course notes for the uploaded document on **Applications in Computational Biology** from **Data Mining**:
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## **Deleteriousness Prediction**
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- **Objective**: Assess whether a genetic variant, specifically a missense variant (which causes amino acid changes), is deleterious (harmful).

β€Žtheme/custom.css

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font-display: swap;
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font-style: normal;
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font-weight: 300;
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format("truetype");
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font-family: "LXGW WenKai Mono";
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font-style: normal;
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font-weight: 400;
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src: url("/fonts/LXGWWenKaiMono-Regular.ttf") format("truetype");
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@font-face {
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font-display: swap;
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font-family: "LXGW WenKai Mono";
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font-style: normal;
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font-weight: 700;
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src: url("/fonts/LXGWWenKaiMono-Medium.ttf") format("truetype");
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}
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:root {
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--font-family: "Libre Baskerville", "LXGW WenKai", serif;
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--font-family-monospace: "JetBrains Mono", "LXGW WenKai Mono", monospace;
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pre,
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font-size: var(--code-font-size);
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β€Žtheme/fonts/LXGWWenKai-Light.ttf

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β€Žtheme/fonts/LXGWWenKai-Medium.ttf

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β€Žtheme/fonts/LXGWWenKai-Regular.ttf

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β€Žtheme/highlight.js

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