1.8 Representation Power of functions

Why do we need complex functions ?

Recap: Six jars

What we saw in the previous chapter?

(c) One Fourth Labs

None of them handle non-linear separable data

Why do we care about continuous functions ?

(c) One Fourth Labs

Recap: Continuous Functions

\(w_{t+1} = w_{t} - \eta \Delta w_{t} \)

\(b_{t+1} = b_{t} - \eta \Delta b_{t} \)

\( \Delta w_{t} = \frac{\partial L}{\partial w} \)

\( \Delta b_{t} = \frac{\partial L}{\partial b} \)

\( \hat{y} = \frac{1}{1+e^{-(2* x_1 +5)}} \)

\( \hat{y} = \frac{1}{1+e^{-(-2* x_1 + 2*x_2+20)}} \)

\( \hat{y} = sig_1(sig_2(x_1,x_2),sig_3(x_1,x_2),sig_4(x_1,x_2)) \)

*sig == sigmoid

Modeling Complex Relations

Why do we need complex functions ?

(c) One Fourth Labs

\( x_1 \)

\(x_2\)

Screen Size

Cost

3.5

4.5

8k

12k

\( \hat{y} = \hat{f}(x_1,x_2) \)

\( \hat{y} = 1\)

\( \hat{y} = 0 \)

\( \hat{y} =\hat{f}(\hat{y_1},\hat{y_2},\hat{y_3},\hat{y_4}, w_9, w_{10}, w_{11},w_{12}, b_{5} )\)

\( \hat{y_2} = \hat{f}(x_1,x_2,w_3,w_4,b_2) \)

\( \hat{y_1} = \hat{f}(x_1,x_2,w_1,w_2,b_1) \)

\( \hat{y_3} = \hat{f}(x_1,x_2,w_5,w_6,b_3) \)

\( \hat{y_4} = \hat{f}(x_1,x_2,w_7,w_8,b_4) \)

Modeling Complex Relations

Why do we need complex functions ?

(c) One Fourth Labs

\( \hat{y} = \hat{f}(x_1,x_2) \)

\( \hat{y} =\hat{f}(\hat{y_1},\hat{y_2},\hat{y_3},\hat{y_4}, w_9, w_{10}, w_{11},w_{12}, b_{5} )\)

\( \hat{y_2} = \hat{f}(x_1,x_2,w_3,w_4,b_2) \)

\( \hat{y_1} = \hat{f}(x_1,x_2,w_1,w_2,b_1) \)

\( \hat{y_3} = \hat{f}(x_1,x_2,w_5,w_6,b_3) \)

\( \hat{y_4} = \hat{f}(x_1,x_2,w_7,w_8,b_4) \)

\( \hat{y} = \frac{1}{1+e^{-(w_1* x_1 + w_2*x_2+b)}} \)

\(w_1\)

\(w_2\)

\(x_2\)

\(x_1\)

\( \hat{y} \)

Are such complex functions seen in most real world examples ?

 

If so, how do I even come up with such complex functions?

Modeling Complex Relations

Are such complex functions seen in most real world examples ?

(c) One Fourth Labs

Adult Census Income\( ^{*} \)

Whether Annual Income of person \( \geq \) 50k or \( < \) 50k ?

Age
90
54
74
45
hour/week
40
40
20
35
Education year
9
4
16
16
Income
0
0
1
1

\( \hat{y} = \hat{f}(x_1, x_2, .... ,x_{14}) \)

\( \hat{income} = \hat{f}(age,hour, ...,education) \)

Modeling Complex Relations

Are such complex functions seen in most real world examples ?

(c) One Fourth Labs

Indian Liver Patient Records\( ^{*} \)

 whether person needs to be diagnosed or not ?

Age
65
62
20
84
Albumin
3.3
3.2
4
3.2
T_Bilirubin
0.7
10.9
1.1
0.7
D
0
0
1
1

\( \hat{y} = \hat{f}(x_1, x_2, .... ,x_{10}) \)

\( \hat{D} = \hat{f}(Age, Albumin, .... ,T\_Bilirubin) \)

Modeling Complex Relations

Are such complex functions seen in most real world examples ?

(c) One Fourth Labs

*https://www.kaggle.com/c/titanic/data

Titanic: Machine Learning from Disaster\( ^{*} \)

Predict survival on the Titanic

Ticket class
93.85
-141.22
-65.2
142.4
# of siblings
83.81
-81.79
-76.33
137.03
Fare
20.1
-52.28
-76.23
93.65
Survived ?
0
1
0
1

\( \hat{y} = \hat{f}(x_1, x_2, .... ,x_{9}) \)

\( \hat{D} = \hat{f}(ticket\_class, fare, .... ,age) \)

Modeling Complex Relations

How do we even come up with such complex functions ?

(c) One Fourth Labs

Class 1

Class 1

Class 1

Class 2

Class 2

Class 2

Class 1 : \( y^2 - x^2 + x^3/8 - y^3/6 > 0 \)

Class 2 : \( y^2 - x^2 + x^3/8 - y^3/6 \leq 0 \)

Class 1 : \( x^2*y + y^3*x > 0 \)

Class 2 : \( x^2*y + y^3*x \leq  0\)

Class 1: \( y - x*sin(x) > 0 \)

Class 2 : \( y - x*sin(x) \leq 0 \)

It's hard to come up with such functions. We need a simple approach!

Modeling Complex Relations

How do we even come up with such complex functions ?

(c) One Fourth Labs

Class 1

Class 1

Class 1

Class 2

Class 2

Class 2

Modeling Complex Relations

How do we even come up with such complex functions ?

Class 1

Class 2

\( f(x_1,..,x_n)  = \frac{1}{1+e^{-(w_1*x_1 + ... + w_n*x_n + b)}} \)

\( f(\bold{x},\bold{w})  = \frac{1}{1+e^{-(w*x + b)}} \)

\(w_1\)

\(w_n\)

\(x_n\)

\(x_1\)

\( f(\bold{x},\bold{w}) \)

\(x_1\)

\(x_n\)

\(\bold{h}\)

Modeling Complex Relations

How do we even come up with such complex functions ?

Class 1

Class 1

Class 1

Class 2

Class 2

Class 2

\( f(x_1,..,x_n)  = \frac{1}{1+e^{-(w_1*x_1 + ... + w_n*x_n + b)}} \equiv \)

\( f(\bold{x},\bold{w})  = \frac{1}{1+e^{-(w*x + b)}} \equiv \)

(c) One Fourth Labs

Take-aways

How to distribute your work through the six jars?

(c) One Fourth Labs

 

\( \in \mathbb{R} \)

loss = \sum_i (y_i-\hat{y_i})^2
Accuracy=\frac{\text{Number of correct predictions}}{\text{Total number of predictions}}

Loss

Model

Data

Task

Evaluation

Learning

Real inputs

\( w = w + \eta \frac{\partial L}{\partial w} \)

\( b = b + \eta \frac{\partial L}{\partial b} \)

Classification

Take-aways

What was all this leading up to ?

(c) One Fourth Labs

Accuracy

Data

\( w = w + \eta \frac{\partial L}{\partial w} \)

\( b = b + \eta \frac{\partial L}{\partial b} \)

Task

Model

Loss

Learning

Evaluation

1.8 Final Draft

By Shubham Patel

1.8 Final Draft

  • 586