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Results tagged with machine-learning
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user 331223
Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervised learning, etc. ALWAYS ADD A MORE SPECIFIC TAG.
2
votes
1
answer
194
views
Interpretation of $\mathcal{D}$ and difference between the accuracy parameter and training e...
I am studying the book "Understanding Machine Learning:
From Theory to Algorithms". They introduce the following things, which I'm not sure i'm interpreting correctly:
The training error(p35) $$L_S(h) …
- 309
2
votes
0
answers
29
views
Why is the inequality true? How do I interpret $\mathcal{D}^m(\{S:L_{(\mathcal{D},f)}(A(S))\...
I am studying the book "Understanding Machine Learning:
From Theory to Algorithms". I am struggling to understand the solution to exercise 3 (2) on page 41.
Exercise:
An axis aligned rectangle classi …
- 309
5
votes
1
answer
279
views
Describe a situation where a training point can be removed without affecting the resulting 1...
I have the following question in my textbook:
One of the drawbacks of the nearest-neighbour algorithm is that
we must retain all of the training data. Describe a situation
where a training point can b …
- 309
1
vote
0
answers
79
views
Sample complexity and VC dimension
I'm studying VC-dimension and sample complexity, and I'd like to understand whether I understand it correctly via the following example.
Let $X = \mathbb{R}$ and $\mathcal{H} = \{ h_{\theta}(x)=\text{ …
- 309
2
votes
0
answers
220
views
Derive the criterion for minimizing the expected loss when there is a general loss matrix an...
In the book "Pattern Recognition and Machine Learning" I am trying to do exercise 1.23 (p.63):
Derive the criterion for minimizing the expected loss when there is a general
loss matrix and general pr …
- 309
3
votes
1
answer
96
views
Resources on on-line machine learning
I am wondering if there are any books/articles/tutorials about "on-line machine learning"?
For example, this website has nice lecture notes (from lec16) on some of the aspects:
https://web.eecs.umich. …
2
votes
1
answer
353
views
Rewriting the Ridge Regression coefficients
In Ridge Regression we try to find the minimum of the following loss function:
$$\text{min}_w\mathcal{L}_{\lambda}(w,S)=\text{min}\lambda\|w\|^2+\sum^l_{i=1}(y_i-g(x_i))^2$$
Where:
$\lambda$ is a pos …
- 309
3
votes
1
answer
209
views
Pattern Recognition and ML Exercise 1.4
I am studying "Pattern Recognition and Machine Learning" by Christopher Bishop and I'm trying to understand his solution in the solution manual to exercise 1.4.
The problem statement for exercise 1.4 …
- 309
5
votes
1
answer
2k
views
Boosting reduces bias when compared to what algorithm?
I am reading on bagging and boosting, and I understand how they both work (at least I think I do). I would like to talk in the context of decision tree ensembles as I think (not sure if correct) that …
- 309
6
votes
1
answer
248
views
True Error in Machine Learning
I have read this question and I am confused by a part of the first answer, even though it is asked in the comments.
I don't understand why $$L_{(\mathcal{D}, f)}(h^{*}) = 0 \implies L_{S}(h^{*}) = 0$$ …
- 309