Decision Tree using C4.5 Algorithm Solved Numerical Example | C4.5 Solved Example by Mahesh Huddar

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  • Опубліковано 29 жов 2024

КОМЕНТАРІ • 26

  • @Krishna-z1g5r
    @Krishna-z1g5r 6 місяців тому +1

    Thank you very much you saved my life very good explanation you are a legend

    • @MaheshHuddar
      @MaheshHuddar  6 місяців тому

      You're welcome!
      Do like share and subscribe

  • @tejakarpuramswaroop4229
    @tejakarpuramswaroop4229 Рік тому +10

    Organizing the content in a structured manner according to a typical syllabus for machine learning can help in understanding the progression of topics. Here's a suggested organization based on common machine learning syllabi:
    Machine Learning Syllabus Structure
    1. Introduction to Machine Learning
    Video 7: Introduction to Machine Learning Definition Examples Applications of ML Why so popular by Mahesh Huddar
    2. Fundamentals and Concepts
    Video 10: Concept Learning Concept Space Hypothesis Space Distinct Hypothesis Space Machine Learning Mahesh
    Video 11, 12, 13: FIND S Algorithm - Solved Examples by Mahesh Huddar
    Video 15: Consistent Hypothesis | Version Space | List Then Eliminate Algorithm by Mahesh Huddar
    3. Learning Algorithms - Decision Trees
    Video 25, 26, 27, 28: How to find Entropy Given Probabilities, Information Gain, Gain in terms of Gini Index, and How to find Entropy | Information Gain | Gain in terms of Gini Index | Decision Tree by Mahesh Huddar
    Video 29, 30, 31, 32: ID3 Decision tree Learning Algorithm - Solved Numerical Examples by Mahesh Huddar
    Video 36: How to Avoid Overfitting in Decision Tree Learning | Machine Learning | Data Mining by Mahesh Huddar
    Video 37: How to handle Continuous Valued Attributes in Decision Tree | Machine Learning by Mahesh Huddar
    4. Clustering Algorithms
    Video 5: K Means Clustering Algorithm | K Means Solved Numerical Example Euclidean Distance by Mahesh Huddar
    Video 92, 93: DBSCAN Clustering Algorithm Solved Numerical Example in Machine Learning Data Mining Mahesh Huddar
    5. Neural Networks
    Video 48, 49, 50: Perceptron Training Rule for AND, OR Gates | Artificial Neural Networks Machine Learning by Mahesh Huddar
    Video 56, 57, 58, 59, 60: Back Propagation Algorithm Artificial Neural Network Algorithm Machine Learning by Mahesh Huddar
    Video 51: Perceptron Rule to design XOR Logic Gate Solved Example ANN Machine Learning by Mahesh Huddar
    6. Instance-based Learning and K-Nearest Neighbors
    Video 106, 107, 108, 109: Solved Examples K Nearest Neighbors Algorithm in Machine Learning by Mahesh Huddar
    Video 111: Locally Weighted Regression Algorithm Instance-based learning Machine Learning by Dr. Mahesh Huddar
    7. Model Evaluation and Validation
    Video 162, 163, 164: Confusion Matrix and Performance Metrics in Machine Learning by Mahesh Huddar
    Video 172: K-Fold Cross Validation, Stratified K-Fold, Leave-one-out, Leave-P-Out Cross Validation by Mahesh Huddar
    8. Text Classification and NLP
    Video 90: Agglomerative Hierarchical Clustering Single link Complete link Clustering by Dr. Mahesh Huddar
    Video 183: Sentiment Analysis using Dictionaries SentiWordNet SentiWords and VADER by Dr Mahesh Huddar
    9. Dimensionality Reduction
    Video 4: Principal Component Analysis | PCA | Dimensionality Reduction in Machine Learning by Mahesh Huddar
    10. Association Rule Mining
    Video 149, 150, 151: Solved Examples Apriori Algorithm to find Strong Association Rules Data Mining Machine Learning by Mahesh Huddar
    11. Ensembling Techniques
    Video 128: Ensemble Learning Techniques Voting Bagging Boosting Random Forest Stacking in ML by Mahesh Huddar
    12. Miscellaneous Topics
    Video 39: Splitting Continuous Attribute using Gini Index in Decision Tree Machine Learning by Mahesh Huddar
    Video 180: Z-Score based Outlier or Anomaly detection and Removal in machine learning by Mahesh Huddar
    This structure follows a typical progression from introductory concepts to more advanced topics, covering fundamental algorithms, evaluation techniques, and applications. Adjustments can be made based on specific syllabus requirements and depth of coverage needed for each topic.

    • @MaheshHuddar
      @MaheshHuddar  Рік тому +3

      Thank You
      I will check and re-organise the content

  • @moonyy5815
    @moonyy5815 7 місяців тому

    Thank you so much sir for explaining so easily 😊

    • @MaheshHuddar
      @MaheshHuddar  7 місяців тому +1

      Most welcome
      Do like share and subscribe

  • @mifteqar7
    @mifteqar7 7 місяців тому

    Thank you so much sir.. i got it😍

    • @MaheshHuddar
      @MaheshHuddar  7 місяців тому

      Welcome 👍
      Do like share and subscribe

  • @ModelDancer-jt3to
    @ModelDancer-jt3to 3 місяці тому

    Thank you sir

    • @MaheshHuddar
      @MaheshHuddar  3 місяці тому

      Welcome
      Do like share and subscribe

  • @Tubenew734
    @Tubenew734 Рік тому +1

    sir can you arrange these lecture according to time wise

  • @binarysaiyan9389
    @binarysaiyan9389 7 місяців тому +1

    Kindly provide the link to the datasets

  • @nicoleta-vw3ql
    @nicoleta-vw3ql Рік тому +1

    Big thanks!

  • @shashanksinghal8395
    @shashanksinghal8395 Рік тому +8

    what exactly is the difference between id3 and c4.5 algorithm except dividing with split_info?

    • @erkanturan7215
      @erkanturan7215 10 місяців тому +3

      id3 can only deal with discrete values whereas c4.5 is extended to also be able to deal with numerical values

    • @Mahadevkikrupa
      @Mahadevkikrupa 8 місяців тому

      No difference

    • @harshinibhat8524
      @harshinibhat8524 6 місяців тому

      There in ID3 we will not calculate split info and gain ratio here extra step is calculating gain ratio and split info

  • @pranaviammineni2005
    @pranaviammineni2005 5 місяців тому

    Sir id3 and c4.5 are different

  • @shobhitupadhyay4711
    @shobhitupadhyay4711 Рік тому

    w sir i got exam tmrw T_T

  • @moen129
    @moen129 2 дні тому

    m

  • @salihatekfa9913
    @salihatekfa9913 11 місяців тому +1

    Thank you very much you saved my life good explanation you are a legend

    • @MaheshHuddar
      @MaheshHuddar  11 місяців тому

      Welcome
      Do like share and subscribe

    • @KuldeepSharma-tn9nw
      @KuldeepSharma-tn9nw 7 місяців тому

      ​@@MaheshHuddar What is the value of log2 here?

    • @devsutong
      @devsutong 5 місяців тому

      @@KuldeepSharma-tn9nw Its not a value, it is a function, specifically binary logarithm (log base 2)