Scatter Plot
Ready Module in AZMLS
For removing an outlier , we can use sql transformation to update any row or values
Why use matplotlib agg
https://matplotlib.org/faq/howto_faq.html
Setting utlier to threshhold ,
By using Clip Values , upper na dlower threshold can be set.
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clip-values
Convert to Indicator Values
to add a column IsCategoricalValue 0 or 1 based on the no of values in the selected feature
Supervised Learning
Nearest neighbour, Naïve Bayes, Decision Trees, Regression
UnSupervised Learning
K- means Clustering Algorithm
ReInforcement Learning
The machine/ software agent trains itself on a continual basis based on the environment it is exposed to, and applies it’s enriched knowledge to solve business problems.
Markov Decision Process
“A computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E.” -- Tom Mitchell, Carnegie Mellon University
Ready Module in AZMLS
For removing an outlier , we can use sql transformation to update any row or values
Why use matplotlib agg
https://matplotlib.org/faq/howto_faq.html
Setting utlier to threshhold ,
By using Clip Values , upper na dlower threshold can be set.
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clip-values
Convert to Indicator Values
to add a column IsCategoricalValue 0 or 1 based on the no of values in the selected feature
Supervised Learning
Nearest neighbour, Naïve Bayes, Decision Trees, Regression
UnSupervised Learning
K- means Clustering Algorithm
ReInforcement Learning
The machine/ software agent trains itself on a continual basis based on the environment it is exposed to, and applies it’s enriched knowledge to solve business problems.
Markov Decision Process
“A computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E.” -- Tom Mitchell, Carnegie Mellon University
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