Machine Learning part 5: mixed methods

#5 mixed methods

Machine Learning

👉 ♡ supervised learning
♡ unsupervised learning
♡ reinforcement learning

types of supervised learning

✔ classification 🗒

✔ regression 📈

✔ mixed ⚗
– tree based
– random forest
– neural networks
– support vector machines

mixed methods are used for classification and regression.

🌱 tree based method

 those trees used for both for classification and regression are called Classification And Regression Trees (CART) models

let us say that we want to predict whether an event will be good or bad, the event being having a good day at school

our data looks as follows

t. represents teacher
a means abscent
p means present

mood stands for parents’ mood
g good. b bad

hwork means homework
d done
nd not done

t. | mood | hwork | result
—————————————
a |      g    |       d    |      g
p |      b    |       d    |      g
a |      g    |     nd    |      g
a |      b    |       d    |      b
p |      b    |     nd    |      b
a |      g    |     nd    |      g
p |      b    |       d    |      g
a |      g    |      nd   |      g
a |      g    |       d    |      g

let us say that today the student entered the school. he wants to know how his day will go, today he has

t.           p
mood   g
hwork  nd

about splitting

the first step is to split the tree to get a high purity index

if we split by teacher’s presence first, we get

a
good 5 bad 1
p
good 2 bad 1

if we split by parents’ mood we get

g
good 5 bad 0
b
good 2 bad 2

if we split by homework done we get

d
good 4 bad 1
nd
good 3 bad 1

the highest index of purity was with parents’ mood with good 5 and 0 bad day

we start with it

mood
—  g
a |      g    |       d    |      g
a |      g    |     nd    |      g
a |      g    |     nd    |      g
a |      g    |      nd   |      g
a |      g    |       d    |      g

good 5 bad 0

— b
p |      b    |       d    |      g
a |      b    |       d    |      b
p |      b    |     nd    |      b
p |      b    |       d    |      g

good 2 bad 2

so bad mood must be split further as good mood had 100% purity with 5 good result

now our condition is

t.           p
mood   g
hwork  nd

if we go for mood g, we can stop spliting as our purity is 100%. we’ll get a good day

next:
〰 enthropy and gain
🌱 random forest
🌱 support vector machines (SVM)
🌱 neural networks

  •  
  •  
  •  
  •  
  •  
  •  

Lives in Mauritius, cruising python waters for now.