Perform Regression using Python Code for Continuous Variables and Logistic Regression for Categorical to predict "Avg_Latency" contributors (uniq_vol))

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Would like to understand the relationship between variables and predict "Avg Latency"

Sample Data - [login to view URL]

Dependent Var: avg_latency (Trying to predict)

Independent Vars (Continuous): read_ops, write_ops, other_ops, read_MB, write_MB, read_latency, write_latency, other_latency

Independent Vars (Categorical): Timestamp, uniq_vol

On the time variable, you can convert this to a quantitative variable. If you wanted to look at day of week, you could assign numeric values like Sunday=1, Monday=2, etc. And same for hour, you could use the 24 hour clock to assign a numeric value to each hour to include this as a variable in your model.

On the uniq_vol variable, this is a bit more complicated. Probably the best way (but very time consuming) would be to create a variable for each possible value and then assign 0 or 1 to each of those variables where for each data point, you would give a value of 1 to the uniq_vol category that data point has and then assign 0 to all the other category variables.

Machine Learning (ML) Python Analisis Statistik

ID Projek: #17128595

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roshansanthoshh

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edecena75

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inspiredwhiz

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Icic13

Hi I've gone through your data. To do a regression and logistic regression the quantitative variable can be converted using one hot encoding then using step wise regression a suitable best model can be selected. After Lagi

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arkahome

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nasirudeen2015

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