Methods and principles of building "computer systems that automatically improve with experience."

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15 views

Ratio between training error and validation error

I know that we should choose the model which minimizes validation error. But is there any meaning of ratio between training error and validation error? I was wondering if it tells something about ...
2
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0answers
25 views

How do I use weight vector of SVM and logistic regression for feature importance?

I have trained a SVM and logistic regression classifier on my dataset for binary classification. Both classifier provide a weight vector which is of the size of the number of features. I can use this ...
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0answers
29 views

Is large scale PCA even possible?

The PCA algorithm assumes that the input matrix columns are with mean zero. This can be achieved easily, but when the input matrix is sparse, the centered matrix will now longer be sparse, and will ...
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0answers
39 views

Is SVM still an active research area?

Recently I am learning SVM classification and regression, I found that most of the work are proposed in the 2000s, (around 2004~2007), but I don't understand why people stop developing it(do they?), ...
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3answers
78 views

Can Random Forest be used for Feature Selection in Multiple Linear Regression?

Since RF can handle non-linearity but can't provide coefficients, would it be wise to use Random Forest to gather the most important Features and then plug those features into a Multiple Linear ...
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2answers
58 views

Why are SVMs hard to fit?

I often hear the following complaint from people: "SVMs work really well WHEN they actually work." By "work" I mean that the algorithm will actually finish running. Are SVMs difficult to fit in ...
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1answer
35 views

Logistic regression is appropriate? Forecasting player’s serve point win % as a binary variable, w/ both numeric and categorical independent variables

I effectively want to model the probability of a player winning his service point (a point in which he is the server) based on the values of explanatory variables (namely court surface and opponent ...
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0answers
9 views

Getting prob of class using naive bayes

I am trying to classify input with two classes, here is the simple code for the same. dino and crypto are two classes ...
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8 views

Convolution network configuration problem

I'm trying to get accuracy information from a convolutional net. If I choose classification I get an output like this: ...
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12 views

Detecting Gibbs Sampler convergence with Raftery and Lewis Diagnostic

Hi! I'm trying to understand and implement the Raftery and Lewis Diagnostic for detecting the number of iterations required for a gibbs sampler but cant seem to understand the formula. ...
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2answers
26 views

Why we need to extract a lot of features from a dataset for classification

I am newbie in machine learning. I have been studying about features extraction and some classification approaches, in the term of my study, I have a question in my mind, what the reasons we need to ...
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0answers
23 views

Running repeated cross-validation for multiple models using same dataset (caret package)

I'm currently using the train() function in the caret package to run 10-fold repeated cv on a random forest model. I would also like to explore other statistical and machine learning models for use ...
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17 views

How to extend independent significance features test to multiple classes?

I have found this post about feature selection using the independent significance features test. There is also an implementation provided. Unfortunately it only works for 2 classes but I have 4 ...
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21 views

Where to find Wikipedia's wiki.dat for LDA, an example used in Vowpal Wabbit? [on hold]

I am following Vowpal Wabbit's tutorial on LDA (Latent Dirichlet Allocation) found here. wiki.dat is used in it as a Wikipedia corpus or supplementary Wikipedia dictionaries, maybe. It must be ...
1
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1answer
53 views

Training a random forest in R with a maximum false positive rate

I ran the following code in R: rf.classifier.master <- randomForest(my_response ~ ., data=feature.matrix) print(rf.classifier.master) and got the following ...
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1answer
47 views

Standardization before applying ANOVA?

I have a matrix where the rows are the data points (samples) and the columns are the features. It is a multiclass (4 classes) problem. On this data I want to apply machine learning classifiers. But ...
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0answers
19 views

Perceptron Learning Algorithm: what is the probability that the viewed data is linearly separable, after some number of steps?

My understanding is that the PCA: will not converge if the data is not linearly separable might take exponentially many iterations, even if the data is linearly separable I'm wondering if, after ...
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0answers
25 views

Label outliers for anomaly detection

I am trying to detect anomalies using unsupervised learning techniques. However, I have the problem that it is impossible to generate controlled anomalies to use as a test set. My idea is to discover ...
1
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1answer
15 views

What should be the covariance matrices and weights for initializing EM/GMM with kmeans?

It's typical to initialize EM for Gaussian Mixture Models using the result of kmeans clustering. However, kmeans only gives you the means (centers) of the starting GMM, but EM initialization often ...
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0answers
15 views

How can I obtain the Simulations in CausalImpact package? [on hold]

Currently we are using your package CausalImpact to evaluate the effect of different interventions over the accident occurrence in different firms. I address to you in order to ask you if there is any ...
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2answers
84 views

Why is linear regression different from PCA?

I am taking Andrew Ng's Machine Learning class on Coursera and in the below slide he distinguishes principal component analysis (PCA) from Linear Regression. He says that in Linear Regression, we ...
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18 views

How to perform Sensitivity Analysis of Bayesian network using R?

I know there are similar techniques for Sensitivity Analysis for Random Forests. I am looking for something similar for Bayesian Networks. I have built the Bayesian Network using bnlearn package in R. ...
1
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1answer
20 views

Pre-training in deep convolutional neural network?

Have anyone seen any literature on pre-training in deep convolutional neural network? I have only seen unsupervised pre-training in autoencoder or restrcited boltzman machines.
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0answers
16 views

What is the difference between a conditional random field model and a particle filter?

Please can any one explain the difference between a CRF model and a particle filter?
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19 views

Issues in Testing SMO SVM

I am new be in SVM and SMO algorithm, I implemented SMO using the pseudocode provided in : “Fast training of support vector machines using SMO” by John platt. I am finding issues testing my ...
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1answer
64 views

Which language best to use for Machine Learning library? [on hold]

We have a body of theoretical work on nearest neighbors that we would like to implement and make the code publicly available. Question: what's the best language to use? We're considering java, python, ...
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2answers
44 views

“Non-naive” bayesian classification algorithms

Based on the problem description in this post: Relating parameters to a measured variable Based on a suggestion, I thought of studying the relationship between the parameters and a measured metric ...
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0answers
19 views

Why multivariate distribution is used to model weights (polynomial coefficients) for prior distribution?

Lately, I have been reading Chris Bishop's work on Bayesian linear regression. What was difficult to understand is why is he models $w_0$ and $w_1$ using multivariate Gaussian distribution in prior ...
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23 views

Classifier that learns provided by only positive examples?

I was wondering if any of you has ever worked with classification/regression using only positive examples (one class). I would need such a system. The basic idea is that it is going to accurately ...
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2answers
29 views

Online learning that “forgets” older aspects learned? (short-term memory)

I am looking for an online learning classifier that is highly adaptable and has only short-term memory. I need such a think in a object tracking system with high-dimensional feature vectors. Maybe a ...
1
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1answer
33 views

The relationship between adaboost and gradient boosting

I am reading the chapter 10 of "The Elements of Statistical Learning 2nd ed, (ESLII)", where the Adaboost algorithm is explained by minimizing the exponential loss using stagewise additive modelling ...
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17 views

How large should the sample be to start using batch gradient descent versus normal equation

Suppose you want to train a multivariate linear regression on an n x m dataset. The runtime of determining your parameter theta = (theta0, theta1, ..., thetam) using the normal equations is ~ O(m^3), ...
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1answer
25 views

How do I “split” Gaussian mixture components when training EM/GMM based classifier?

In order to improve performance of my Gaussian Mixture Model based classifier, I was recommended to start with a single multivariate Gaussian, estimate its parameters, and "split" it into two ...
3
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0answers
31 views

SVM with non-negative weights

An SVM classifier can be obtained by solving the following, $\arg\min \frac{1}{2}\|W\|_2^2 + C\sum_i \max(0, 1-y_i (W^T\mathbf{x}_i + b))$ where $W$ is the hyperplane (or weights), $b$ is the bias, ...
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15 views

How to add cluster centers to the already transformed arrays with T-SNE Scikit Learn?

let's get this scikit original code, which is basically the one I'm using. My X is 2000x100 and in order to plot the clusters (plot on the right) I want to transform it with with the TSNE algorithm ...
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1answer
23 views

does sklearn rbm scale well with sparse high dimensional features

i am using scikit learn's RBM implementation. There are two problems: The running time is O(d^2) where d is the number of features. This becomes a problem in using high dimensionality sparse ...
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0answers
9 views

normalized mutual information implantation in java for community detection in graph range is not between 0 and 1 [closed]

I write a program for calculating normalized mutual information for evaluate community detection. but i get values above 1 for nmi. normally it should be between 0 and 1. i implement formula in ...
0
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1answer
38 views

How to get probability from the confidence score in SVM

In liblinear library we can get confidence score (the distance between decision hyperplane) in SVM solver for a binary classification problem, but if i want a probability value for membership in any ...
0
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1answer
42 views

Is ROC or PR curve only the overall performance measure for classification

We can use ROC or PR curve to access the performance of the classifier,especially on imbalance data. But it is a curve with parameter threshold, even if we get a high ROC or PR performance, which ...
0
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0answers
13 views

How to use KL-divergence in naive bayes classifier to weight features?

I have a dataset consisting of 4 classes. I have implemented the Gaussian Naive Classifier (in Matlab). In the training phase I calculate the mean and variance for each feature and each class as well ...
3
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1answer
33 views

What's the measure to assess the binary classification accuracy for imbalance data

Now I have binary classification problem with positive samples roughly 100 times the number of negative samples. In this case the normal accuracy measure (predict == label) is not a good measure. What ...
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11 views

Does theano support multi-machine version [closed]

We use theano in the GPU in a single machine, I am just wondering if it supports multi-machine programming so that the speed will raise up?
2
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0answers
35 views

Finding idf only for text mining

We find tf-idf for training phase in text mining, however, in test phase, we need the tf for each element in test set, but should use idf in train set, so is there any api in python that can calculate ...
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0answers
12 views

Inversely proportional version of a nearest-neighbour results vector - how?

Short version: Given an input vector D of n values, what are the different methods that one can use to return a vector W such that each value in W is in inverse proportion to the magnitudes of the ...
0
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0answers
21 views

tf-idf in text mining

I used sklearn of Python for getting tf-idf attribute in text analysis, but the problem is: I have about 78000 words in train_set, but the tf-idf matrix only has 39000 words. What is the problem ...
0
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0answers
18 views

How to use Weight vector of SVM and logistic regression for feature importance?

I have trained a SVM and logistic regression classifier on my dataset. Both classifier provide a weight vector which is of the size of the number of features. I can use this weight vector to select ...
0
votes
0answers
34 views

how can I fixed size of grid search in libsvm?

I'm trying to use libsvm to classify a database that contains 1000 labels using svm one vs rest . My goal is to get out the probabilities for each class and to perform accuracy. I know that the first ...
0
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1answer
26 views

What are the differences between delta rule and generalized delta rule?

I know that the delta rule is a gradient decent learning rule. But, what are the differences between these two delta rules? Thanks in advance.
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19 views

IKAnalyzer in text mining

Does anyone use IKAnalyzer for word segmentation in the preprocess for text mining? I have never loaded my own extended dictionary or stopword dictionary successfully. The following is the ...
3
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1answer
25 views

How to use log probabilities for Gaussian Naive Bayes?

I'm currently implementing a Gaussian Naive Bayes classifier. Of course if I'm doing classification by $$ \text{argmax}_{C_i} P(C_i)P(D|C_i), $$ then the probabilities can get very small. So I want ...