课程: Machine Learning with Scikit-Learn
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Which machine learning model should you use? - scikit-learn教程
课程: Machine Learning with Scikit-Learn
Which machine learning model should you use?
- [Instructor] With so many machine learning algorithms available from scikit-learn, which algorithm should you choose? Selecting a good enough model from among a large number of possible machine learning models is one of the hardest parts of machine learning. Some algorithms are better suited to different types of data and problems. Luckily, a quick answer to model selection with scikit-learn is, use the algorithm cheat sheet. It's meant to give you a rough guide in how to choose an algorithm. From the start point, you first ask, do you have more than 50 samples? From there, you keep on answering questions until you get an idea of what you should try. If you don't use the cheat sheet, here are a few things to consider when choosing a model. The first thing is a problem you're trying to solve. For example, if you have a supervised learning problem, figuring out if you're trying to predict a continuous or categorical value…
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内容
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What is supervised learning?54 秒
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How to format data for scikit-learn1 分钟 55 秒
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Linear regression using scikit-learn4 分钟 32 秒
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Train test split1 分钟 53 秒
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Logistic regression using scikit-learn3 分钟 55 秒
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Logistic regression for multiclass classification3 分钟 36 秒
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Decision trees using scikit-learn3 分钟 9 秒
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How to visualize decision trees using Matplotlib2 分钟 5 秒
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Bagged trees using scikit-learn2 分钟
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Random forests using scikit-learn2 分钟 41 秒
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Which machine learning model should you use?1 分钟 23 秒
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