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WEEK 9: Write a program to implement SVM algorithm to classify the iris data set. Print both correct and wrong predictions.

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  WEEK 9:      Write a program to implement SVM algorithm to classify the iris data set. Print both correct and wrong predictions. πŸ‘‰ Student Handout πŸ‘‰ Program πŸ‘‰ Colab πŸ‘‰ YouTube Link

MACHINE LEARNING USING PYTHON LAB

  MACHINE LEARNING USING PYTHON LAB Course Outcomes: At the end of the course the student should be able to: 1.      Select data, model selection, model complexity and identify the trends. 2.      Understand a range of machine learning algorithms along with their strengths and weaknesses. 3.      Build predictive models from data and analyze their performance. List of Experiments WEEK 1 : a)      Write a program using scikit-learn to implement K-means Clustering b)      Program to calculate the entropy and the information gain c)      Program to implement perceptron. WEEK 2: ·        Implement and demonstrate the FIND-S algorithm for finding the most specific hypothesis based on a given set of training data samples. Read the training data from a .CSV file. WEEK 3: ·        Fo...

Machine Learning MCQs

  Machine Learning MCQs πŸ‘‰1.  Machine Learning MCQs - UNIT 1 πŸ‘‰2.  Machine Learning MCQs-2 (Performance Metrics, Linear Regression, NaΓ―ve Bayes Classifier ) πŸ‘‰3.  Machine Learning MCQs-3 (Logistic Regression, KNN, SVM, Decision Tree) πŸ‘‰4.  Machine Learning MCQs - 4 (Clustering, Dimensionality Reduction) πŸ‘‰5. Machine Learning MCQs - 5 (Ensemble Models)

Support Vector Machines

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  Predicting Date Fruit Varieties with Support Vector Machines Context Objective is to leverage advanced machine learning techniques to predict the variety of date fruits, empowering farmers and agricultural stakeholders to improve classification accuracy and streamline post-harvest processes. Your role is to analyze various morphological, colorimetric, and textural attributes of date fruits to build predictive models that distinguish different varieties effectively. Dataset Description You have been provided with a comprehensive dataset containing morphological and colorimetric features of different varieties of date fruits. The dataset includes the following attributes: Morphological Attributes: AREA:  Surface area of the date fruit. PERIMETER:  Perimeter measurement around the fruit. MAJOR_AXIS:  Length of the major axis of the date fruit. MINOR_AXIS:  Length of the minor axis of the date fruit. ECCENTRICITY:  Ratio descri...