Tagged Questions

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

learn more… | top users | synonyms

0
votes
0answers
25 views

What are the advantages of deep convolutional neural network over shallow one?

I know that deep convolutional neural network(cnn) helps reducing the number of free parameters in training. What are other advantages of using deep cnn over shallow cnn?
0
votes
1answer
12 views

Can we learn 3d features using Autoencoder?

Typically, we use Autoencoder to learn 2d features on 2d images (e.g. pen-strokes of digit). For example, if I have 10000 3d 31x31x31 images (e.g. car images). I unroll each of the images, i.e. ...
0
votes
0answers
13 views

Naive Bayes Produce Confidence

I am pretty newbie in machine learning. Please forgive and point out anyone incorrect use of terminology. Now I am learning Naive Bayes algorithm. As I have learned Neural Network, when predicting, ...
4
votes
3answers
196 views

When should I apply feature scaling for my data

I started a discussion with a collague of mine and we started to wonder, when should one apply feature normalization / scaling to the data? Lets say that we have a set of features with some of the ...
1
vote
1answer
18 views

Why AUC-PR increases when the number of positives increase?

I asked a question earlier about comparing models using Precision-Recall AUC. One of the answers included the following statement: "The larger the fraction of positives in the data set, the larger the ...
1
vote
1answer
37 views

What are some useful robust and scalable approaches towards anomaly detection of a time series data?

What are some useful robust and scalable approaches/methods towards anomaly detection of a time series data? I am mainly looking for some practical approaches carried out using Python, R, Java, etc. ...
1
vote
2answers
43 views

Comparison of machine learning algorithms

Suppose i have taken 8 machine learning algorithm which is used researchers more frequently.I have applied these 8 machine learning algorithm over 8 datasets which is publickly available on internet. ...
2
votes
0answers
14 views

How to approach a bag-of-words classification when each word has a 'loudness' parameter?

Suppose that I want to perform a binary classification on voice data, classifying sentences as having a positive/neutral or negative sentiment.The language I'm working with only has 50 words total and ...
1
vote
1answer
19 views

Ranking two models based on ROC-AUC and PR-AUC

I have two methods/classifiers (completely different models) that I need to decide which one is better. The dataset is imbalanced. I trained both classifiers on the same dataset and then I computed ...
2
votes
1answer
20 views

Is it correct to use Precision-Recall AUC in a balanced dataset situation?

I have a binary classification scenario with a dataset that is unbalanced (much more negatives than positives). When I train a classifier on this dataset I get a Precision-Recall AUC of 0.7. Then I ...
0
votes
0answers
14 views

How to calculate the area under the precision-recall curve for the random classifier?

I know that the random classifier score in ROC AUC (Area under the curve) is always 0.5. My question is: how to calculate the Area under the precision-recall curve for the random classifier?
1
vote
0answers
17 views

why pretraining for convolutional neural networks

Usually Back propagation NN has the problem of vanishing gradients. I found that Convolutional NN (CNN) some how get rid of this vanishing gradient problems (why?). Also in some papers some ...
0
votes
0answers
19 views

How to plot a precision-recall curve when doing cross-validation?

I'm using cross-validation to evaluate the performance of a classifier with scikit-learn and I want to plot the Precision-Recall curve. I found an example on ...
0
votes
0answers
12 views

Optimizing selection from varying sets

On pages of website(s) I have a set of potential messages to choose from and only one or two slots to show them in. (think 'this product is on sale' or 'this product is new'). On each page the set ...
0
votes
0answers
19 views

What does “shift invariant” mean in convolutional neural network?

I saw a term describing the feature detectors, i.e. shift invariant. What is that mean? Paper: 1989 Generalization and Network Design Strategies
0
votes
0answers
21 views

Should a BoxCox transformation to normalize the skewness of data be applied to all the predictors?

If there are few predictors that are highly skewed among a larger set of predictors in case of a linear regression problem, should a BoxCox transformation be applied to only these few predictors or ...
0
votes
1answer
17 views

How do search engines generate related searches?

I would like to know how search engines like Bing generate related searches when the user starts typing into the search box. From what I gather, there has to be some sort of a ranking algorithm where ...
0
votes
1answer
16 views

Which Machine Learning algorithm: Sorted list of tags given metadata?

Our system allows an admin to manage a database of university courses. These courses have multiple fields, like the department, a title, and a description. I am adding the ability to add learning ...
0
votes
0answers
24 views

clustering analysis of large amount of time series

I would like to cluster a set of time series, which are composed of around 50000 different time series. Are there established algorithms/package that can handle this scalability problem?
0
votes
0answers
4 views

Function approximation, inverting and finding input values subsets based on output value

Suppose I have a set of input/output values for some unknown and complex function which I want to approximate using some machine learning algorithm. The input variables are integers or reals. The ...
0
votes
0answers
23 views

Merging two disconnected graphs

Firstly, I'd like to apologize for any misused terms or ways I could have made the description much more succinct. It's been a while since I took machine learning during my bachelor's. I have two ...
0
votes
0answers
10 views

Does the gamma hyperparameter have any affect on a polynomial SVM?

I am using sklearn and its SVM implementation - But I was wondering whether the gamma parameter was a parameter exclusive to the rbf kernel; since the gamma parameter indicates the width of the ...
0
votes
0answers
12 views

SVM - RFE for nonlinear case

Could someone give me some reference or idea on how to implement SVM-RFE for nonlinear cases. As we all know that SVM RFE for linear case is well established by Guyon et al. for (gene) selection where ...
0
votes
0answers
17 views

Support Vector Machine with zero bias term

I'm looking for an algorithm to solve SVM with zero bias term. So dual form of such SVM is $max_\alpha \sum_i^n \alpha_i -1/2\sum_i^n \sum_j^ny_iy_jK(x_ix_j)\alpha_i\alpha_j$ subject to: $0 \leq ...
1
vote
1answer
39 views

Temperature prediction using NN and SVM

I am trying to develop a NN or SVM model to predict surface temperature based on several features such as air temp, humidity, wind speed, sunshine etc. I have collected data so I do have the true ...
8
votes
2answers
209 views

What is a log-odds distribution?

I am reading a textbook on machine learning (Data Mining by Witten, et al., 2011) and came across this passage: ... Moreover, different distributions can be used. Although the normal ...
0
votes
0answers
8 views

Using t-test for feature selection after z-scoring data?

Suppose I have a high-dimensional dataset, and a binary classification problem. I want to use the two-sample t-test for feature selection. If the data has been normalized by z-scoring (so it has zero ...
0
votes
0answers
12 views

What is divergence in indicators/oscillators?

What is the direct cause of divergence in indicators/oscillators? Is it because of using the close price? How could I filter it out or isolate it? This would be useful to extract for a predictive ...
0
votes
0answers
21 views

(binary) Matrix completion with less known data

Recently, I meet such problems, I call it matrix completion problem. For example, the row denotes the users and the column denotes items. And If one user like the ...
0
votes
0answers
8 views

How do I install and use Shogun toolbox in matlab? [closed]

I want to use Shogun toolbox in matlab (windows) but their installation guide is not clear. Does anyone know simple steps to install shogun toolbox in matlab?
0
votes
0answers
12 views

The Shogun Machine Learning toolbox for SVM with precomputed kernel and zero bias

Can I use the Shogun Machine Learning toolbox for SVM with precomputed kernel and zero bias. I should be able to input pre-computed kernel and I also should be able to set bias zero.
0
votes
0answers
11 views

SVM with pre-computed kernel and zero bias

I have an optimization function, where I need to give my own kernel matrix and bias value is zero. The kernel matrix is calculated using the data but there is no specific formula for it. If I have a ...
0
votes
2answers
83 views

Machine Learning and Biostatistics [closed]

I am interested in a few areas with biostatistics, and was reading the course catalog at a university that offers machine learning. I am taking topology now, and i think machine learning uses ...
0
votes
0answers
53 views

Probabilistic model Vs Weight based model

Can someone please explain what is the difference between probabilistic model vs weight based model with respect to ML context. When to use one over the other?
1
vote
1answer
33 views

Multi Output Neural Networks

Up until know I only used neural networks to classify a single output, I set one output neuron for each class and check which neuron has the highest/lowest activation. What I am trying to do is to ...
0
votes
0answers
24 views

Neural Network for hand written digit recognition

I have create the neural network with three layers. 1 layer - 500 inputs 2 layer - 500 inputs 3 layer - 10 output classes. I have synthesized the ...
1
vote
1answer
38 views

Glmnet Caret Package with small number of observations

I have a regression problem where I’m attempting to train a data set with 70 predictors, but only 35 observations with glmnet in the caret package. I’m trying to determine the best resampling method. ...
1
vote
2answers
47 views

Time Series Anomaly Detection with Python

I need to implement anomaly detection on several time-series datasets. I've never done this before and was hoping for some advice. I'm very comfortable with python, so I would prefer the solution be ...
-1
votes
0answers
14 views

How to create a feature vector with scikit-learn? [closed]

I have extracted some bigrams from a corpus, how can i create a feature vector with those bigrams with scikit-learn?, could anybody provide me some example?. Thanks
2
votes
0answers
24 views

Why does glmnet in caret give different predictions for different alphas even though lambda is zero?

In R, when using caret to train an elastic net regularization model, I find that different values of alpha give different predictions when the lambda parameter equals zero. This should not be the ...
4
votes
1answer
34 views
+50

How to measure when error stabilizes (convergence) on Random Forests (or, when do I stop training)

I'm doing an implementation of Random Forests. As I was the original paper (page 11) and this nice book on the subject (15.3.1, page 592), they mention that when the out-of-bags error stabilizes (when ...
1
vote
1answer
38 views

What is considered to be “good” classification rate?

Let's say I am trying to figure out whether two classes can be differentiated. My methods may not be perfect, but I would like to know whether my features "mean" anything that may possibly be added to ...
1
vote
0answers
17 views

How do we get/define filters in convolutional neural networks?

How do i obtain filters from convulutional neural network(CNN)? My idea is something like this: Do random images of the input images (28x28) and get random patches (8x8). Then use autoencoders to ...
0
votes
0answers
3 views

How to account for different ratio of samples during training and detection using a support vector machine (svm)?

Consider the following object recognition case: Detection of objects in an image using a sliding window approach in combination with a svm model. During sliding window search using multiple scale ...
0
votes
0answers
11 views

How to find a good model for an object recognition case using a support vector machine (svm)?

Consider the following example of an object recognition case: I'm trying to detect objects in an image using histograms of oriented gradients (hog) features. The feature vector resulting from hog is ...
1
vote
0answers
30 views

Building a predictive model, regression with a long right tail

I am trying to build a, regressive, predictive model for a target time-series that is heavily skewed. You could think of the target as being like earthquake magnitudes or heavy rainfall. Most of the ...
1
vote
1answer
33 views

Does Deep network (e.g. # of hidden layer=2) always better than shallow network (i.e. # of hidden layer=1)?

I attempted to build a deep network (e.g. deep autoencoder) for some object classification, my result showed that the deep networks is worst than shallow network. However, from what I have read from ...
0
votes
0answers
22 views

How to CORRECT un-reliable and un-stability in the prediction results

Currently, I meet such questions when building Random Forest model using my data set. My full data set: X_lab: 839 * 469 and y_lab: 839 * 1 which is for all labelled data and X_unl: 20346 * 469 which ...
0
votes
0answers
11 views

Practical problem computing de k-nearest neighbors in CF?

I’m trying to apply de knn to a very dynamic system where users (like/dislike) items very frequently and new items became available all the time. My question is how often should the algorithm ...
0
votes
0answers
15 views

Regarding Naive Bayes and conditional independence

We all have been talking about how Naive Bayes may, in some cases, not perform well due to the fact that this assumes conditional independence of features and MOSTLY, this is not true for real world ...