Lesson 3 - Supervised learning Flashcards
1
Q
Supervised Learning formalization
A
- Input: x∈X, X is the space of instances of the task
- Output: y∈Y, changes depending on the task:
- classification, binary
- multi-class classification, natural numbers
- regression, real numbers
- we assume that an oracle exists
- the training data is composed from historical records (x, y), generated by the oracle
- an hypothesis is selected from an hypothesis space using training data
2
Q
Types of oracle
A
- Oracle deterministic
- a function associates input and output
- target function is deterministic and unknown
- Oracle stochastic
- input and output chosen according to a certain probability distribution
- target function is stochastic and unknown
3
Q
Training set
A
A series of pairs, generated according to a probability function
4
Q
Empirical error/risk
A
- error on training data
5
Q
Ideal error/risk
A
- expected error on a given pairs x, y drawn according to the probability distribution
6
Q
Characteristics of the selected hypothesis
A
- a plausible hypothesis is selected using training data
- it should generalize well
- correct predictions also for unseen examples
7
Q
Inductive bias
A
- assumptions made on hypothesis space and learning algorithm
- hypothesis space cannot contaion all possible functions
- how the space is explored