Methods and principles of building "computer systems that automatically improve with experience."
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44 views
How to calculate entropy in log Scale?
I'm working on a problem , where a function returns the Log probability of P(X=x) . Now I would like to find the Entropy of X. But since the probabilities I get are log probabilities, again taking its ...
0
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0answers
101 views
Fitting a logistic regression using lassoglm in matlab
I am fitting a logistic regression model using lassoglm in matlab. I issued the following command
...
0
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0answers
48 views
Classifying high-dimensional data
I'm only learning about classification but why is it common practice to use PCA before using a Support Vector Machine?
Assuming I have 128*10 features and only 90 datapoints for each, do I need to ...
0
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0answers
9 views
Recall Precision curve, precision jumps at high recall [duplicate]
I am trying to plot a recall-precision curve for an object detection algorithm. In order to detect objects, I create a vote-map (2D histogram) in which object centres are voted for.
I then filter ...
0
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1answer
165 views
How to calculate recall-precision curves
I am trying to plot a recall-precision curve for an object detection algorithm. In order to detect objects, I create a vote-map (2D histogram) in which object centres are voted for.
I then filter ...
0
votes
1answer
160 views
understanding of libsvm output
I applied libsvm to build a text classifier. The output looks like as follows:
...
2
votes
1answer
162 views
Predicting Football match winners based only on previous data of same match
I'm a huge football (soccer) fan and interested in machine learning too. As a project for my ML course I'm trying to build a model that would predict the chance of winning for the home team, given the ...
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0answers
40 views
Which level of abstraction is appropriate when designing a Hidden Markov Model?
Bear with me, it is all new to me.
I have measured a thing repeatedly over a period of time and I have clustered the results. (Clustered the measured values without the time information.) The ...
0
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0answers
77 views
Wavelets and machine learning
I am trying to learn features from a signal using Wavelet transform and then apply ML techniques on it to classify a signal. The problem I am facing is that, at each of level of decomposition, my ...
3
votes
1answer
76 views
Variable importance randomForest negative values
I am asking myself if it is a good idea to remove those variables with a negative variable importance value ("%IncMSE") in a regression context. And if it gives me a better prediction? What do you ...
-1
votes
1answer
43 views
How does Logistic regression classifier modelize the dataset?
I'm working on a system that be able to detect the hand contour. So I have 270 instance in my dataset: 7 class of hand contour, 8 feature vectors of each instance.
Firstly, I used Weka to determine ...
0
votes
1answer
192 views
ROC curve and confusion matrix in classifier performance evaluation
I applied two different classifiers against the same validation set. It turns out that classifier A is better than classifier B in terms of ROC curve. However, classifier B is better than classifier ...
2
votes
0answers
137 views
Matrix factorization and gradient descent for recommender systems; user bias?
I've been reading about using Matrix Factorization techniques to do collaborative filtering. A popular thing to do seems to be to add user and item biases into the ratings prediction. What I don't ...
0
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0answers
30 views
Can very large numbers of samples throw off Naive Bayes?
I'm writing what is effectively a spam filtering system. I have about three million samples, mostly bag-of-words and top-tfidf based samples, and I'm seeing abysmal precision and recall. I'm trying to ...
2
votes
1answer
171 views
Logistic regression as classifier and overfitting
I am using logistic regression to classify data into two classes. The variable to predict (Y) is either 0 or 1.
I have found a rather good estimation of Y by logistic regression, and ended up using ...
0
votes
0answers
85 views
Description of all models in R's caret package? [closed]
I've been looking into machine learning recently, mostly using R. I just came across the caret package and it seems to be brilliant for quickly trying out different models. It seems a great tool for ...
1
vote
1answer
64 views
Derivation of the posterior over topics in LDA
When studying the latent Dirichlet allocation, I am not very clear about some procedures in their deriving equations. Please refer to the attached figure, how to understand those two steps, marked as ...
0
votes
2answers
43 views
difference in training and testing procedure of model
Can anyone please tell me the difference in training and testing of a model. I have developed 5/6 different single pass online learning algorithm (ets, ets+, evolving fuzzy modelling, SOFNN, ...
3
votes
1answer
95 views
Decision tree : handle attribute with many nominal values
I would like to build a decision tree from a training data. I have an attribute with many nominal values. For example, the department name attribute has about 20-30 values. I would like to group ...
0
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0answers
92 views
How to compute precision for a multiclass problem?
I have a question about calculating precision on a multiclass problem. If the true positives of some actual class is 0, and its false negatives is also 0, then how to calculate its recall? In this ...
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0answers
89 views
Predicting twitter activity using time series analysis
I'm interested to build a model for predicting how many tweets people I follow will probably tweet today (or by hour), based on their previous tweets in the last 60 days (or more).
Of course that the ...
1
vote
1answer
62 views
Non-independence of IVs in a random forest model
How is a random forest model affected if some of the variables are not independent?
0
votes
1answer
94 views
Choosing a better data-set
I have two data-sets for same samples. But they are produced using two different instruments. I want to choose one data-set for further analysis. How can I find/prove which data-set is better?
To ...
3
votes
0answers
90 views
Using priors to detect an effect? logistic Bayesian regression
I have designed an idea and am looking for similar approaches in other literature/areas or if I have applied the Bayesian concepts wrongly. Here is a statement of my problem:
I am modeling the ...
0
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0answers
37 views
Form field identification
I am working on a problem in which given a form (mostly scanned) one needs to automatically detect all the fields and their corresponding values from it. The information that I have is location of ...
2
votes
1answer
126 views
Using the appropriate machine learning algorithm
I am not sure if this is the right forum to ask this.
I have some data of the houses, like their size(in square meters), if they use aircondition, how many residents live in, I have their electricity ...
1
vote
1answer
119 views
what should be the parametric form of the l2 regularization in a Bayesian setting?
In a Bayesian setting for parameter estimation, what should be the parametric form of the prior distribution in order to perform l2 regularization?
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0answers
176 views
How helpful is a quant job in Goldman Sachs for later PhD in Machine Learning?
I am a masters in Computer Science and am interested in pursuing a career in Machine Learning, possibly academic, in the long run.
I have been offered a position related to Financial Modelling at ...
2
votes
0answers
78 views
Random Forest or other machine learning techniques with paired samples
I am trying to select features from paired samples and was wondering if there are methods out there that adapt random Forest or other machine learning algorithms to paired samples i.e. if randomForest ...
0
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0answers
41 views
May I get HMM calculations Checked?
I was trying to understand Hidden Markov Model(HMM). I was working out some examples.
The first work out was on initial probability, transition probability and emission probability.
I was trying to ...
0
votes
3answers
174 views
Binary classification machine learning
I have
data set (30,000) mapping people to incomes(<=some number ,>some number)
each instance has 15 features so as age, education.
I would like some advice/pointers as to the best machine ...
1
vote
4answers
167 views
Neural networks for simplistic image classification
I want to train a neural network to classify a few simple, cartoony images like the ones below (for the moment I only have the classes house, tree, and sword).
The images I am (currently) using ...
2
votes
1answer
45 views
How can I estimate a score for my users, on if they will match ad campaign criteria?
I have ad campaigns that I want to display to users. Each one has criteria a user must meet in order for them to be valid for the campaign. For example, "User must be in the USA", or "User must like ...
0
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0answers
51 views
Online Linear Regression with updates on past information
Suppose we have the following algorithm
An online linear regression algorithm implemented using gradient descent. The step rate $\alpha$ is calculated using something that correlates to the squared ...
0
votes
0answers
51 views
Are my HMM calculations going fine? [closed]
I was trying to understand the hidden Markov model (HMM) and to do some calculations, and I got some doubts. I attach my study in this Google Drive File.
Can you check if my calculations are fine?
I ...
1
vote
1answer
45 views
Inconsistency in cross-validation results
I have a set of dataset recorded from subjects as they perform some particular cognitive task. The data consists of 16 channels and a number of sample points per channel and I want to classify this ...
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0answers
24 views
Classifying foreground vs background for ellipse shapes
I have images of ellipse shapes which are read in as a matrix of pixel intensities. I'd like a way to be able to classify whether a pixel is foreground (belonging to ellipse) or background (not ...
0
votes
0answers
45 views
How to solve a dilemma case on Support Vector Machine?
I am learning the SVM classification and especially interested in applying to medical data. Now, I encounter a problem and do not know if this dilemma has a terminology for it.
Assume that there ...
3
votes
1answer
106 views
Graphical representation of cross-validation errors for regression
What are some good ways of presenting/comparing cross-validated RMSE errors for regression using various models, graphically via plots? As of now, I have been presenting the quantitative results in ...
0
votes
1answer
62 views
liblinear one vs rest learn parameters
Liblinear (http://www.csie.ntu.edu.tw/~cjlin/liblinear/) does not support for probability estimates.
Say I have three classes C1, C2 and C3. I want to learn the model paramters for each 'one vs rest' ...
1
vote
1answer
36 views
Generating rules to obtain a given categorical distribution… is it possible?
I'm working on a problem, I was wondering if there are any methods available to do the following.
I have a data set with information on people (continuous and categorical data). I have 3 categories ...
1
vote
1answer
123 views
Weighted covariance matrix using kernels
I would like to create a weighted covariance matrix (say 5 variables) using 3 different time points where the weights come from a kernel function (can be normal, triangular, etc.) but I'm not ...
0
votes
0answers
36 views
Is there a theoretical basis for the shrinkage used in Boosted Regression Trees?
In Gradient Boosted Regression Trees, a shrinkage $\nu$ is often applied as:
$$ f_t(x) \leftarrow f_{t-1}(x) + \nu h(x)$$
where $h$ is the regression tree learned by fitting the tree to the gradient. ...
4
votes
2answers
775 views
how to calculate precision and recall for multiclass classification using confusion matrix?
all, I wonder how to compute the precision and recall using confusion matrix for multi-class classification problem. In specific, one data can only be assigned with most probable class/label.
I like ...
5
votes
2answers
331 views
What is the difference between a neural network and a deep belief network?
I am getting the impression that when people are referring to a 'deep belief' network that this is basically a neural network but very large. Is this correct or does a deep belief network also imply ...
2
votes
0answers
49 views
Some examples of errors in ESL?
I am reading the book The Elements of Statistical Learning (Hastie et al, chapter 7) and I am confused about the different kinds of errors mentioned in the book
Test error $$Err_\tau=E(L(y, ...
0
votes
1answer
129 views
Pocket algorithm for training perceptrons
When you read about perceptron variants at Wikipedia there is explained an algorithm: Pocket Algorithm It is said that:
solves the stability problem of perceptron learning by keeping the best ...
1
vote
2answers
121 views
Data whitening for improving regression
My Data: $X_i= \{0.4;~7;~1,000;0;~0.8;~1;~0;~40;~0.7;~1;~0;~89,100\},~Y_i=345$ The training set size is $\approx35, 000$. $Y$ is the dependent variable and the task is to estimate its value ...
1
vote
0answers
184 views
Machine Learning Algorithms vs. Linear Regression
Do machine learning algorithms like Boosted Regression Trees (in the R package (gbm)) follow the same statistical assumptions of not including correlated predictor variables in GLM?
i.e. If I have ...
0
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0answers
60 views
Forming training set for Multinomial Naive Bayes
Is it true that Multinomial Naive Bayes requires equally by count training data for each class to get best performance?
For example, we forming classifier for three classes - Japan, China, Korea.
...
