PySpark Tutorial 34: PySpark Decision Tree | PySpark with Python

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PySpark Tutorial 34: PySpark Decision Tree | PySpark with Python

About this video: In this video, you will learn how to about decision tree in pyspark

Large Language Model (LLM) - LangChain

Large Language Model (LLM) - LlamaIndex

Machine Learning Model Deployment

Spark with Python (PySpark)

Data Preprocessing (scikit-learn)

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very nice teaching method. thanks a lot for sharing such a great tutorial

naseemfiver
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Thanks for the video. Why petal width not given importance?

bhavinmoriya
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you have showed us the predictions, can you tell us how to compute the error rate e.g Incorrectly Classified Samples’ divided by `Classified Sample

and also if you can teach us how to calculate the sensitivity and specifity.

akshanthhirani
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do you do videos for support vector machine model in python sparky

akshanthhirani
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how to caluculate f1 measures and recall please help me

vamshikrishna
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hi. @ 8:59 i get this error when trying to do the df_classifier, and the error is:
IllegalArgumentException: requirement failed: Classifier found max label value = 52.0937 but requires integers in range [0, ... 2147483647).


i am not using the same csv file as you but a very similar one


can you try and help me

jameshenwood
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