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What is the best way to implement an SVM using Hadoop?

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The best way to implement SVM using Hadoop is by using **Apache Mahout** or **Hadoop Streaming** with libraries like **LibSVM**, which facilitate distributed SVM training and execution on Hadoop clusters.
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Online Mathematics tutor with 4 years experience(Online Classes for 10th to 12th)

Import the Libraries- Load the Dataset. Split Dataset into X and Y. Split the X and Y Dataset into the Training set and Test set. Perform Feature Scaling. Fit SVM to the Training set. Predict the Test Set Results. Make the Confusion Matrix.
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  1. Import the Libraries-
  2. Load the Dataset.
  3. Split Dataset into X and Y.
  4. Split the X and Y Dataset into the Training set and Test set.
  5. Perform Feature Scaling.
  6. Fit SVM to the Training set.
  7. Predict the Test Set Results.
  8. Make the Confusion Matrix.
read less
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Wroking in IT industry from last 15 years and and trained more than 5000+ Students. Conact ME

Use Apache Mahout for SVM on Hadoop, leveraging its distributed machine learning algorithms.
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