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
–Â 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