The learning tag has no wiki summary.
1
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0answers
39 views
Kalman- Bucy filter: prior mean change
I have a question on Kalman-Bucy filter:
the prior distribution is $g \sim N(0,σ_g^2 )$, signal is $ds=(μ+g_t )dt+σdZ_t$, posterior distribution becomes $g_t \sim N((\hat{g_t},\hatσ_t^2)$. ...
2
votes
1answer
30 views
When to normalize learning?
I'm trying to determine the effect of three types of learning on a group of subjects.
I have their pretest scores and posttest scores.
The current goal is to determine which intervention reduce the ...
0
votes
1answer
124 views
R statistics output interpretation : ebook
I am basically a biologist working in genomics data analysis
I have started learning statistics and now am acquainted with basics of it. I can run several statistics commands on R.
I have plenty of ...
0
votes
0answers
11 views
Evaluate performance of feature
I'm doing a project on image classification. Given satellite images, I want to classify them into either urban or rural area.
I picked a few features, and now how to evaluate it's performance ...
3
votes
2answers
180 views
Estimating the covariance posterior distribution of a multivariate gaussian
I need to "learn" the distribution of a bivariate gaussian with few samples, but a good hypothesis on the prior distribution, so I would like to use the bayesian approach.
I defined my prior:
$$ ...
0
votes
2answers
162 views
Recommendations for learning probability and Bayesian statistics? [duplicate]
I have been very interested lately in learning Bayesian Statistics, but I have only a little bit of background in the frequentist statistics, only one term at University.
Some of the books that I ...
1
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0answers
56 views
Is it advantageous to use dummy variables when learning a regression model?
Say I have 3 random variables ${X, Y, Z}$, and I have collected an iid sample of size $N$ from them: ${\cal D} = \{ (x_i, y_i, z_i), i = 1,\dots,N \}$.
The conditional expectation $E[ X | y ]$ can ...
3
votes
1answer
137 views
Sparse representations for denoising problems
I have read in a huge number of papers that sparse models (sparse coding, dictionary learning, sparse matrix factorization, ...) are good solutions for image denoising problems.
I know that ...
2
votes
0answers
23 views
Generalization error for classification with a nonconvex loss function
I've been working my way through Vapnik's 1998 Statistical Learning Theory book and one thing that I'm still unsure of is if his risk bounds hold for nonconvex loss functions -- i.e., when we can't be ...
1
vote
1answer
88 views
Mixed effect and learning curves
My question might be too simple but I just started to do statistical analysis and use R and is not always simple!
I have performance data for 5 subjects with different level of experience, repeating ...
4
votes
2answers
168 views
Sources for learning (not just implementing) statistics/math through R
I am interested in examples of sources (R code, R packages, books, book chapters, articles, links etc) for learning statistical and mathematical concepts through R (it could also be through other ...
2
votes
2answers
106 views
Data analysis “quizzes” [duplicate]
Possible Duplicate:
Locating freely available data samples
Sites for predictive modeling competitions
Are there sites or sources of "datasets" (either artificially created or taken from ...
4
votes
1answer
187 views
Evaluation of classifiers: learning curves vs ROC curves
I would like to compare 2 different classifiers for a multiclass text classification problem that use large training datasets. I am doubting whether I should use ROC curves or learning curves to ...
11
votes
4answers
717 views
Is a strong background in maths a total requisite for ML?
I'm starting to want to advance my own skillset and I've always been fascinated by machine learning. However, six years ago instead of pursuing this I decided to take a completely unrelated degree to ...
2
votes
1answer
76 views
How to determine the best number of weak classifiers to use in adaboost without overfitting the data
I was thinking by using validation but not quite sure how to go with it. Please list some papers or ideas on how. This is for multiclass problem (using one vs all approach). I think each ...
2
votes
6answers
285 views
Recommend an enjoyable / introductory book on Statistics [duplicate]
Possible Duplicate:
A resource on concepts underlying statistics, not the techniques used in applied stats
I am interested in learning more about Statistics and when I ran a Google / Amazon ...
2
votes
1answer
89 views
Under what conditions can a PLS regression model be expressed by single linear equation?
I am confused by two, yet inconsistent for me, facts: Since the PLS regression is expressed by matrices of scores and loadings as
$$X=TP^T+E\\Y=UQ^T+F$$
how it can be translated into linear equation ...
3
votes
2answers
175 views
Goals for students in an introductory course
I am studying Statistics for business at introductory level, and having difficulty in handling the amount of information, partly because I am coming back to study after 5 years and I didn't do much ...
1
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0answers
94 views
The genuine inventors of concepts
General:
It is almost a permanent need in researching progress addressing/referring the first inventor, proposer or developer of the concepts which are widely being used these days. Have got no clear ...
4
votes
2answers
273 views
Training of a Neural Network
I am trying to train an Artificial Neural Network for classification. In the input layers, I have 402 neurons; the first 400 are binary, and the last two are floating points in the range -1 to 1. In ...
4
votes
3answers
569 views
Online material to learn time series analysis
My question is if there are any good online materials for learning this. Something that introduces things well, especially ARMA models and the related math.
Edit: I'm looking for something of the ...
6
votes
3answers
181 views
Learning on huge datasets
Basically, there are two common ways to learn against huge datasets (when you're confronted by time/space restrictions):
Cheating :) - use just a "manageable" subset for training. The loss of ...
14
votes
5answers
2k views
Can you recommend a book to read before Elements of Statistical Learning?
Based on this post, http://quant.stackexchange.com/questions/111/how-can-i-go-about-applying-machine-learning-algorithms-to-stock-markets, I want to digest Elements of Statistical Learning. ...
3
votes
1answer
120 views
When is there a representer theorem?
The case of regularization in a hilbert space is considered---an optimization problem with an error term and a Tikhonov-regularizer.
In the article "When is there a representer theorem" it is stated ...
-1
votes
2answers
253 views
How to figure out the behind concept of statistical-look problems?
The following is my experience doing some researches linked to statistical concepts. In the most situations I had no idea on how to organize the questions, ...
12
votes
4answers
330 views
How to digest statistical context?
Firstly, I suppose that not all active members of this interesting site are statisticians as their job. Otherwise the question being asked as follows does not make any sense! I respect them of course. ...
0
votes
1answer
100 views
How to keep statistical knowledge growing? [closed]
How to keep statistical lessons that we catch growing? Is there any model to learn statistics in a way to get the best use of them in engineering applications? I don't mean recommendations on basic ...
14
votes
11answers
1k views
Best way to get started with and learn R
I have tried several times to "go it on my own" - but with limited success. I am a casual SPSS user and some SAS experience.
Would appreciate a pointer or two from someone who has similar background ...
2
votes
0answers
208 views
Struggling to make headway with Introduction to Probability by Bertsekas & Tsitsiklis [closed]
I'm an academic in biology and I'm trying to improve my working knowledge of probability and probabilistic methods. I was recommended the Introduction to Probability textbook as an excellent ...
10
votes
4answers
552 views
Software (or webapps) for teaching kids statistics or probability?
I would like (in the distant future) to teach statistics to kids. For that matter, I'd be happy to know of software (obviously I am tending towards FOSS), or webapps, that are helpful in explaining ...
9
votes
3answers
393 views
How to transition from using statistical software to understanding mathematical equations in journal articles?
Context:
I'm a Psychology PhD student. As with many psychology PhD students, I know how to perform various statistical analyses using statistical software, up to techniques such as PCA, ...
5
votes
3answers
608 views
Looking for stats/probability practice problems with data and solutions
I am looking for a self-study site on the web that will allow me to verify my understanding of some basic probability and stats concepts and operations.
What I would like is a site with data and ...
32
votes
7answers
2k views
Mathematician wants the equivalent knowledge to a quality stats degree
I know people love to close duplicates so I am not asking for a reference to start learning statistics (as here).
I have a doctorate in mathematics but never learned statistics. What is the shortest ...
14
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2answers
399 views
Statistics, war stories, data intuition
I think it is fair to say statistics is an applied science so when averages and standard deviations are calculated it is because someone is looking to make some decisions based on those numbers. Part ...
8
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2answers
2k views
Resources for learning statistics - exercises (with solutions), available online?
I'm currently working as a teaching assistant at my University, in an introductory statistics course (for medical students).
Offline, there are many books available with information to aid the ...
3
votes
4answers
355 views
How to learn how to use a new statistical GUI?
The question is in the header, but I would extend the context a bit.
Next semester I am due to be a TA in a course in statistics, where I would need to help sociology students learn to use SPSS. I ...
