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

[@salihatekfa9913]

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

[@MaheshHuddar]

Welcome Do like share and subscribe

[@KuldeepSharma-tn9nw]

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

[@devsutong]

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

[@tejakarpuramswaroop4229]

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]

Thank You I will check and re-organise the content

[@moonyy5815]

Thank you so much sir for explaining so easily 😊

[@MaheshHuddar]

Most welcome Do like share and subscribe

[@mifteqar7]

Thank you so much sir.. i got it😍

[@MaheshHuddar]

Welcome 👍 Do like share and subscribe

[@nicoleta-vw3ql]

Big thanks!

[@MaheshHuddar]

Welcome Do like share and subscribe

[@Tubenew734]

sir can you arrange these lecture according to time wise

[@shashanksinghal8395]

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

[@erkanturan7215]

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

[@Mahadevkikrupa]

No difference

[@harshinibhat8524]

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

[@ModelDancer-jt3to]

Thank you sir

[@MaheshHuddar]

Welcome Do like share and subscribe

[@PushpitKamboj]

can anyone tell from which book does sir gives the questions in video ? very important to know

[@binarysaiyan9389]

Kindly provide the link to the datasets

[@alibabarahaei2229]

Perfect

[@geethapanneer101]

Sir for this example python program is there?

[@Anu-qf2ys]

Need answer for id3 same question

[@pranaviammineni2005]

Sir id3 and c4.5 are different

[@MaheshHuddar]

Yes

[@shobhitupadhyay4711]

w sir i got exam tmrw T_T

[@moen129]

m

[@Krishna-z1g5r]

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

[@MaheshHuddar]

You're welcome! Do like share and subscribe