Classification is a predictive modelling task in machine learning where a class label is predicted for a given example of input data. The following are some examples of classification issues: Determine whether or not a given example is spam. Determine which of the known characters a handwritten character belongs to.
Overfitting is not a problem for this performer because he is not influenced by outliers. Not suitable for non-linear problems, and not the greatest option for problems with a large number of features. High performance on non-linear problems, not influenced by outliers, and not overfitting sensitive.
A simple majority vote of each point's k nearest neighbours is used to classify it. It's supervised and uses a collection of identified points to label other points. It looks at the labelled points closest to the new point, usually known as its nearest neighbours, to label it.
The ability to recognise items and categorise them is a typical task for machine learning systems. This is known as classification, and it allows us to categorise large amounts of data into discrete values, such as 0/1, True/False, or a pre-defined output label class.
A classifier is a machine learning method used in data science to assign a class label to a data input. An image recognition classifier, for example, can be used to label a picture (e.g., "vehicle," "truck," or "human").
Learner's Ratings
4.4
Overall Rating
70%
11%
11%
5%
3%
Reviews
R
Rishu Shrivastav
5
explained everything in detail. I have a question learnvern provide dataset , and ppt ? or not?
V
VIKAS CHOUBEY
5
very nicely explained
V
Vrushali Kandesar
5
Awesome and very nicely explained!!!
One importing thing to notify to team is by mistakenly navie's practical has been added under svm lecture and vice versa (Learning Practical 1)
M
Mohd Mushraf
5
Amazing Teaching
J
Juboraj Juboraj
5
Easy to understand & explain details.
J
Joydeb
5
Awesome Course sir and your teaching style is very GOOD.
S
Shaga Chandrakanth Goud
5
Hi Kushal ji, Thanks a lot for a very good explanation. I have doubts about where we can get the dataset that you explained in the video. Can you make it available in resource ,so that we can downld
N
Neel Khairnar
5
Kushal is very good explainer he is covering all topics nicely 👍
Share a personalized message with your friends.