Support Vector Machines (SVM) Overview and Demo using R

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Quick overview and examples /demos of Support Vector Machines (SVM) using R.
The getting started with SVM video covers the basics of SVM machine learning algorithm and then finally goes into a quick demo

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Here is the script used in this video for anyone who doesn't have time to type it out:

library("e1071")
plot(iris)

plot(iris$Sepal.Length, iris$Sepal.Width, col=iris$Species)
plot(iris$Petal.Length, iris$Petal.Width, col=iris$Species)

s<-sample(150, 100)
col<-c("Petal.Length", "Petal.Width", "Species")
iris_train<-iris[s, col]
iris_test<-iris[-s, col]

svmfit <- svm(Species ~., data = iris_train, kernel = "linear", cost = .1, scale = FALSE)
print(svmfit)
plot(svmfit, iris_train[, col])

tuned <- tune(svm, Species ~., data = iris_train, kernel = "linear", ranges = list(cost=c(0.001, 0.01, .1, 1, 10, 100)))
# Will show the optimal cost parameter
summary(tuned)

p <- predict(svmfit, iris_test[, col], type="class")
plot(p)

table(p, iris_test[, 3])
mean(p== iris_test[, 3])

booradleyboo

amazing melvin..what a free flow and for lay man like me ..its easy to understand

kalyanasundaramsp

thank you very much, this video very cleary explanation dan very helpful bro
Keep going
Regards from Indonesia.

andialpacino

Tnk man. You saved me. Grettings from Mexico!

ZxJorge

Really nice, simple and useful code! thank you

paulchabert

Excellent Video! Very well explained! Could you maybe do another one for One-Class SVM?

kobepoprox

“Introduction to Machine Learning With R” O’Reilly books are pretty good

josueperez

attempting to do this on a different data set but cannot identify two classifiers that appear to be linearly separable, any suggestions?

reidhibbard

I really the way the explanation was, it was very good .

krishnakanth

Can we use SVM for time series forecasting? I do not have any feature set other than year, week & sales (in units)...

dipayansarkar

Sir, how to identify the important variables in SVM when we have a set of variables?

shareefamohamed

Good work, does the features (no of features) affect the optimal hyperplane

erigits

You have covered pretty much everything in this video but I guess at some points I need some explanation. If u can please answer my questions.
1) On what basis you actually defined the range values for the cost variable?

2) I was reading their practical guide and I found that 'Gamma' is also as important as 'Cost' but u never discussed anything.

3) I know that at the end we are calculating the mean value which actually representing the system accuracy. Can you tell me what this 'number of vectors' is representing? Like i am solving a two spiral problem so i am getting 130 no. of vectors. I am curious cuz i am just passing 132 rows of data. Is that bad or good ? or how do you interpret?
I would be very thankful to you if you can answer my questions.

mq.

This video was a great help! Thank you!

when I try and view the data in a table instead of in a histogram (near the end of the video), I get an error that "all arguments must be the same length"

nathanyakich

can someone explain the plot step to me? i'm confused on what iris_train[, col] means

shreyaschaturvedi

When I tried to make "iris_train <- iris[s, col]" I got the error "undefined columns selected".

christineanietert

This seems to be inspired from Patrick Winston's lecture on SVM from MIT. Great work nevertheless :)

hariramrajan

i plot my model, but it doesnt display the plot.
plot(modelsvm, dataTrain[, c])
^ modelsvm is same as your svmfit and dataTrain is same as your iris_train and c is same as your col
how did i fix this ?

dandi

how many karnels type that we have for SVM ?

mejab

could you please help me, I have a class with 8 levels. how would I use svm to create the 8 levels ???

cherryberry

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