A brief understanding on supervised learning – Machine Learning

In this tutorial, we will be taking a closer look at supervised learning. supervised learning is a classification type of machine learning.

Machine learning is a very powerful tool for predicting future data by seeing a trend in a given data set. And supervised is a type of classification were in data we have been given output label.

See also,

 



A closer look at Supervised Learning

Supervised learning is again separated into two categories

  • classification
  • Regression

when the output variable is binary then it is termed as a classification problem for example when output is ‘No’ or ‘Yes’.

in addition when the output variable is some real values such as weight and height then is it termed as regression

we will be using kaggle data set for future example graduate-admissions

understanding supervised learning in machine learning

we can see that if a person get

302 102 1 2 1.5 8 0 0

302 GRE score,102 TOFLE scores,1 university,2 SOP, 1.5LOR,8 CGPA,0 research did not get admitted, this type of problem is termed as supervised classification problem were the output label is in binary

while in regression-type problems.

for below, we example we have used kaggle dataset

supervised learning example

from the above example, we can say that the output label which ‘purchase’ is in real number these type of problem is known as a supervised regression problem

Conclusion

In this tutorial, we have learned the following

  • what is supervised learning
  • type of supervised learning
  • classification and regression with example

I hope you got a fair idea about supervised learning, for information I would recommend taking a look Understanding Artificial Neural network (ANN)until then enjoy learning.

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