In classification problem authors always says that knn, naive decision tree are conventional classifiers?
So, can anyone elaborate on the word "conventional" and what are the non-conventional classifiers?
Thanks in advance
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"conventional" here has no specific technical meaning
it just means "models which have been around since such a long time that i leant them at school" !
(so, obviously, the list varies with the age of the author)
.
if i were to use this terminology, and given my age, i would call SVM or random forests "non conventional" ; deep learners would be ultra-non conventional !
(but i shall certainly not use such terminology)
.
.
"conventional" here has no specific technical meaning
it just means "models which have been around since such a long time that i leant them at school" !
(so, obviously, the list varies with the age of the author)
.
if i were to use this terminology, and given my age, i would call SVM or random forests "non conventional" ; deep learners would be ultra-non conventional !
(but i shall certainly not use such terminology)
.
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