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Results tagged with machine-learning
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user 247356
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.
1
vote
0
answers
125
views
in a binary features and one binary output case, is the size of a hypothesis space = $2^{\te...
this post gives a set of observations:
x1 x2 x3 x4 | y
---------------
0 0 0 1 | 0
0 1 0 1 | 0
1 1 0 0 | 1
0 0 1 0 | 1
and claims that
The input space is in the above given example $ …
- 566
1
vote
1
answer
26
views
does $w_1^{n-1}$ denote whole the sentence in the context of word prediction?
this NLP book gives
When we use a bigram model to predict the conditional probability of
the next word, we are thus making the following approximation:
$P(w_n|w_1^{n-1}) \approx P(w_n|w_{n-1} …
- 566
2
votes
1
answer
711
views
In deep learning, what is empirical distribution good for? In the case of applying vgg on mn...
section 3.9.5 of The Deep Learning Book says
\begin{equation}
\hat{p}(x) = \frac{1}{m} \sum_{i=1}^m \delta(x - x^{(i)}) \tag{3.25}
\end{equation}
We can view the empirical distribution formed fro …
- 566
4
votes
2
answers
2k
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Could anyone explain the terms "Hypothesis space" "sample space" "parameter space" "feature ...
I am confused with these machine learning terms, and trying to distinguish them with one concrete example.
for instance, use logistic regression to classify a bunch of cat images.
assume there are 1 …
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5
votes
1
answer
536
views
What does "large grant" mean in machine learning?
Rob Tibshirani, a statistician at Stanford university, created this amusing comparison between machine learning and statistics:
What does "large grant" here mean?
- 566
1
vote
1
answer
52
views
what is the name of this computation?$e_{10}{(0.1)} = 0.8$
section 1.4.3 of the book "Machine Learning - A Probabilistic Perspective" gives an example about KNN:
the input is two dimensional, we have three classes, and K = 10
which contains a computat …
- 566
4
votes
2
answers
2k
views
How to get the false positive? "1 - true negative" or "1 - true positive"?
wiki gives this Drug testing Example to illustrate Bayes' theorem
${\displaystyle {\begin{aligned}P({\text{User}}\mid {\text{+}})&={\frac {P({\text{+}}\mid {\text{User}})P({\text{User}})}{P(+)}}\\&={ …
- 566
1
vote
0
answers
39
views
How to calculate a 𝑛-step transitions of a Discrete-time Markov Chain for Figure 17.1 (b) i...
chapter 17 of the book "Machine Learning - A Probabilistic Perspective" gives this figure
which is the probability of getting from i to j in exactly n steps.
Obviously A(1) = A.
In the case …
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1
vote
1
answer
60
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Can anyone help to explain one of the variables in a figure that illustrates how posterior p...
I am learning this post.
The book gives this figure to illustrate how posterior probabilities shift and move around
Here is the code
%matplotlib inline
from IPython.core.pylabtools import figsize …
- 566