Hfrxdjt

Why doesn't the fusion process of the sun speed up?

If I cast the Enlarge/Reduce spell on an arrow, what weapon could it count as?

How can a new country break out from a developed country without war?

Emojional cryptic crossword

What (if any) is the reason to buy in small local stores?

Print a physical multiplication table

Could any one tell what PN is this Chip? Thanks~

How do you justify more code being written by following clean code practices?

Asserting that Atheism and Theism are both faith based positions

Why is this tree refusing to shed its dead leaves?

Why are there no stars visible in cislunar space?

PTIJ: Which Dr. Seuss books should one obtain?

What will the Frenchman say?

Do I need an EFI partition for each 18.04 ubuntu I have on my HD?

What kind of footwear is suitable for walking in micro gravity environment?

Isn't the word "experience" wrongly used in this context?

Nested Dynamic SOQL Query

Are hand made posters acceptable in Academia?

How to find the largest number(s) in a list of elements, possibly non-unique?

Turning a hard to access nut?

Is this Pascal's Matrix?

Pre-Employment Background Check With Consent For Future Checks

Help with identifying unique aircraft over NE Pennsylvania

Do native speakers use "ultima" and "proxima" frequently in spoken English?

How to categorize machine learning problems, techniques, solutions and algorithms in one super flowchart, consisting of all possible categories?

AWS machine learning prediction schema problemsResearch in high-dimensional statistics vs. machine learning?How do AI's learn to act when the problem space is too bigAlgorithmic approach to model blendingDeciding the number of clusters in K-means clustering of descriptorsAlgorithms and techniques for spell checkingDifference between machine learning and artificial intelligenceUsing Machine Learning techniques for text-analysisHow to handle “unknown” category in machine learning classification problems?What are the common properties of all machine learning algorithms?

0

$begingroup$

I am trying to create a flowchart that categorizes everything under the sun that exists in machine learning. From the different techniques to the evaluation metrics to miscellaneous techniques used to assist machine learning (like stratified sampling, bias, overfitting etc) to categorization of techniques by the problem it solves versus the algorithm it uses. The problem itself seems so vast that iam unable to comprehend the solution. My tries have been pretty basic and resulted in the following :-

Machine Learning Auxillary Techniques (Stratified Sampling, Deciling, Dimensionality Reduction)
Machine Learning Evaluation Metrics (R Square, ROC Curve, Confusion Matrix, Log Loss etc)
Machine Learning Real World Problems (Game Theory, CustomerSegementation/Profiling, Pre Post Campaign Assessment, Genetics etc)
Machine Learning Techniques ( CLustering, Regression, Neural, Bayesian etc)
Machine Learning Problem Types (Supervised/Unsupervised/SemiSupervised/Reinforcement/Continuous/Discrete)

Do you think that these 5 consist of adequate number of categories to entrap the entirety of machine learning in its bounds (of course, with enough number of values for each category, i have listed only a fraction of the total number of techniques). If yes, then where can i get a good guide for helping me in this endeavor? Even a good answer will act as a good guide for me.

Thanks, Abhay

machine-learning data theory

share|improve this question

asked 10 mins ago

Abhay SainiAbhay Saini

1

New contributor

Abhay Saini is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

0

$begingroup$

I am trying to create a flowchart that categorizes everything under the sun that exists in machine learning. From the different techniques to the evaluation metrics to miscellaneous techniques used to assist machine learning (like stratified sampling, bias, overfitting etc) to categorization of techniques by the problem it solves versus the algorithm it uses. The problem itself seems so vast that iam unable to comprehend the solution. My tries have been pretty basic and resulted in the following :-

Machine Learning Auxillary Techniques (Stratified Sampling, Deciling, Dimensionality Reduction)
Machine Learning Evaluation Metrics (R Square, ROC Curve, Confusion Matrix, Log Loss etc)
Machine Learning Real World Problems (Game Theory, CustomerSegementation/Profiling, Pre Post Campaign Assessment, Genetics etc)
Machine Learning Techniques ( CLustering, Regression, Neural, Bayesian etc)
Machine Learning Problem Types (Supervised/Unsupervised/SemiSupervised/Reinforcement/Continuous/Discrete)

Do you think that these 5 consist of adequate number of categories to entrap the entirety of machine learning in its bounds (of course, with enough number of values for each category, i have listed only a fraction of the total number of techniques). If yes, then where can i get a good guide for helping me in this endeavor? Even a good answer will act as a good guide for me.

Thanks, Abhay

machine-learning data theory

share|improve this question

asked 10 mins ago

Abhay SainiAbhay Saini

1

New contributor

Abhay Saini is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

$begingroup$

I am trying to create a flowchart that categorizes everything under the sun that exists in machine learning. From the different techniques to the evaluation metrics to miscellaneous techniques used to assist machine learning (like stratified sampling, bias, overfitting etc) to categorization of techniques by the problem it solves versus the algorithm it uses. The problem itself seems so vast that iam unable to comprehend the solution. My tries have been pretty basic and resulted in the following :-

Machine Learning Auxillary Techniques (Stratified Sampling, Deciling, Dimensionality Reduction)
Machine Learning Evaluation Metrics (R Square, ROC Curve, Confusion Matrix, Log Loss etc)
Machine Learning Real World Problems (Game Theory, CustomerSegementation/Profiling, Pre Post Campaign Assessment, Genetics etc)
Machine Learning Techniques ( CLustering, Regression, Neural, Bayesian etc)
Machine Learning Problem Types (Supervised/Unsupervised/SemiSupervised/Reinforcement/Continuous/Discrete)

Do you think that these 5 consist of adequate number of categories to entrap the entirety of machine learning in its bounds (of course, with enough number of values for each category, i have listed only a fraction of the total number of techniques). If yes, then where can i get a good guide for helping me in this endeavor? Even a good answer will act as a good guide for me.

Thanks, Abhay

machine-learning data theory

share|improve this question

asked 10 mins ago

Abhay SainiAbhay Saini

1

New contributor

Abhay Saini is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

Machine Learning Auxillary Techniques (Stratified Sampling, Deciling, Dimensionality Reduction)
Machine Learning Evaluation Metrics (R Square, ROC Curve, Confusion Matrix, Log Loss etc)
Machine Learning Real World Problems (Game Theory, CustomerSegementation/Profiling, Pre Post Campaign Assessment, Genetics etc)
Machine Learning Techniques ( CLustering, Regression, Neural, Bayesian etc)
Machine Learning Problem Types (Supervised/Unsupervised/SemiSupervised/Reinforcement/Continuous/Discrete)

share|improve this question

asked 10 mins ago

Abhay SainiAbhay Saini

1

New contributor

Abhay Saini is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

share|improve this question

asked 10 mins ago

Abhay SainiAbhay Saini

1

New contributor

Abhay Saini is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 10 mins ago

Abhay SainiAbhay Saini

1

New contributor

Abhay Saini is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 10 mins ago

Abhay SainiAbhay Saini

1