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

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Obtain Precision and Recall from Click through data

I am trying to build a graph of precision and recall using click data. I have two data sources. First data source has all the user clicked item_ids based on a given query_id. Second data source has ...
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28 views

Creating a model for a webshop

I'm going to create a Multi-armed bandit algorithm to handle recommendations for a large scale webshop. I'm going to use Thompson sampling (http://en.wikipedia.org/wiki/Thompson_sampling) and would ...
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1answer
84 views

Why can we assume that samples $X_i$'s are independent if the parameter is fixed (though unknown)?

To put it in context, I was trying to learn Bayesian parameter estimation (by an example of learning the probability of heads of a coin) and was trying to understand the independence of the samples ...
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1answer
545 views

What gradient descent method is better for convolutional neural network?

Let's say we want to train a convolutional neural network, what gradient descent method works better? Batch gradient descent Stochastic gradient descent
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58 views

What is the difference between independent subspace analysis and independent component analysis?

What is the difference between independent subspace analysis (ISA) and independent component analysis (ICA)?
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2answers
367 views

Bayesian Linear Regression

I have the following question concerning Bayesian linear regression on my machine learning assignment: Consider $f = w^Tx$, where $p(w) ∼ N(w | 0, Σ)$. Show that $p(f | x)$ is Gaussian. I ...
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1answer
543 views

What does ROC-EER in percent stand for?

Ive tried to understand what the ROC Curve represents and what EER (Equal Error Rate) means. And I somehow think I got to understand some of the explanations I read on the internet and videos I ...
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85 views

What is weakly-labeled data?

I am afraid I ask an easy question, but here are my questions: What is weakly-labeled data and is there any strongly-labeled data? In what situation do we use them?
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1answer
689 views

Time series with multiple subjects and multiple variables in R

I'm having trouble finding a time series technique to deal with a data set I am working on. It contains multiple subjects and multiple variables, not all of which will likely be part of the time ...
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60 views

Observed versus hidden variables for Bayesian network in this particular context

I am a novice in Bayesian networks. I have a problem which is best described (at least I think so) in the following story. One wants to predict earthquakes. Let's say it has 5 variables, the last one ...
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67 views

When to use K mean clustering and hierarchical clustering algorithm? [closed]

Can you please tell me when to use the K-mean clustering and hierarchical clustering algorithm and what is the different between them... Regards, Rahul
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3answers
148 views

Explanation on a Minsky's critique on statistical learning related to XOR

I was listening to the first session of society of Minds by Minsky (2011) and he mentions at some point around minute 48 the following: "...lots of statistical learning tools is good for lots of ...
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2answers
29 views

Inferring on an unknown number of function approximation

I want to ask whether a procedure to do the following job exists (or whether it makes sense for it to exist). First, assume we have $k$ functions $f_1,...f_k$ that have the same domain and range. ...
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60 views

Find distribution of Bus arrival time

I am currently working on a problem in my research which can be modeled into the following question: Let's say I have a rich dataset with values for the variable $A$ which is equal to ...
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193 views

Machine learning/random forests with noisy response data

Machine learning techniques like random forests seem to assume that the responses in the training set are known perfectly. Specifically for regression applications, it seems one needs to account for ...
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1answer
25 views

Viability of software dev - Use of and requirements of NN

Hello I would like to know this two things regarding the viability of producting a software, so: 1) Are available on internet some OCR libraries for free? Can I train my own NN having only a laptop? (...
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1answer
320 views

What is a good model for revenue managment / price optimization problem

I am trying to create a dynamic pricing model to optimize revenue for a hypothetical business. Lets say I have an application that connects dog walkers to people who want to pay for their dog to get ...
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1answer
68 views

make prediction with HMM

I want to use HMM to make some prediction. say $O$ is the observation, $S$ is the hidden states, and I know how to train the model with forward-backward algorithm. I just get confused with how to ...
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1answer
198 views

K-means clustering feature selection

I have a set of English and foreign language documents that I would to perform k-means clustering on to find document groups by topic. These documents are concatenated social media comments for ...
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3answers
428 views

One model performs better than the other. How to measure if it is statistically significant?

So, let's say that I train two models on the same dataset. I run the experiment once and I get the following results: Using a Neural Network I get an AUC ROC of 0.941. Using Random Forest I get an ...
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2answers
165 views

What is the difference between a neural network and a perceptron?

Is there any difference between the terms "neural network" and "perceptron"?
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1answer
302 views

Are there any contemporary uses of jackknifing?

The question: Bootstrapping is superior to jackknifing; however, I am wondering if there are instances where jackknifing is the only or at least a viable option for characterizing uncertainty from ...
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1answer
342 views

What does the k-value stand for in a KNN model?

What is the k-value in a KNN classification model? Is K the number of Clusters?
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1answer
272 views

Is there AUC for neural network?

I am confused about how to calculate AUC for neural network with a softmax classifier. For example, I know that for SVM, we can change the threshold value and determine the AUC. WHat about in neural ...
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293 views

What are the most interesting, new hot topics in machine learning for seminar and later for thesis? [closed]

I'm in an informatics master student in Palestine Polytechnic University, I have a seminar course this semester i cant decide the topic to search in, especially that i want it to be my thesis topic ...
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126 views

Convolutional Neural Network Performance - Cats & Dogs

I am currently experimenting with a Convolutional Neural Network, trying to get a good performance on the Cats & Dogs challenge at Kaggle. By now, the best result I could get using my network was ...
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2answers
3k views

Why do we divide by the standard deviation and not some other standardizing factor before doing PCA?

I was reading the following justification (from cs229 course notes) on why we divide the raw data by its standard deviate: even though I understand what the explanation is saying, it is not clear ...
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1answer
234 views

Bias/variance tradeoff tutorial

I'm looking for a good tutorial about bias/variance tradeoff. In particular, I'd like to find someone that explains how different algorithms in machine learning play in this tradeoff, and possibly how ...
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1answer
173 views

Summer school on data mining & ML [closed]

I'm a PhD student in Physics and this summer I'd like to attend a one/two weeks summer school on data mining and machine learning. Do you have one to recommend? Thanks!
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1answer
193 views

combining multiple classifiers common features

Can multiple binary-classifiers be combined to produce a final output if their feature sets have some common elements? How will this influence the accuracy?
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2answers
121 views

Emphasize a link between two predictor variables (Machine Learning)

I am creating a machine learning application which will utilize logistic regression (though I haven't ruled out bayesian regression). I have multiple predictor variables that I believe to be non-...
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2answers
577 views

Kernel density estimation vs. machine learning for forecasting in large samples

This is a hypothetical and pretty general question. Apologies if it is too vague. Suggestions on how to better focus it are welcome. Suppose you are interested in the relationship between one ...
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2answers
36k views

How to understand the drawbacks of K-means

K-means is a widely used method in cluster analysis. In my understanding, this method does NOT require ANY assumptions, i.e., give me a dataset and a pre-specified number of clusters, k, and I just ...
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82 views

SVM fusion training data set

For a binary classification problem, I have split the data set into multiple sets and trained each set using a SVM. I want to combine the outputs from each data set using another SVM. What is the best ...
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1answer
76 views

Name and methods for classification with 'unknown' as acceptable result

What is it called when, in a classification task, it is acceptable that some data-points do not receive a label? And what classifiers are suitable? I have a dataset with a two valued target variable. ...
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2answers
98 views

Should image classifier be trained using colormap pixels or the actual value?

For example, I have a population density map of a 100 x 100 km square region. Each part of the rectangular region represents the population density i.e. (1,1) -> 128 people, (100,100) -> 50 people ...
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52 views

Unbalanced groups and classification errors

I would like to adopt a general strategy for dealing with an very unbalanced dataset, where my "positive" group corresponds to 1/40 of all the observations. The reason why I ask it is because all the ...
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2answers
413 views

Using monthly product usage data to predict customer churn

I've been reading tons of papers detailing methods on predicting customer attrition, but none of them have mentioned using product usage data over time. We keep detailed logs of how many times User A ...
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1answer
350 views

Mortgage loan predictive analysis

I have hundreds of thousands of mortgage loan historic records that look like these 2 examples: ...
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2answers
629 views

How to normalize filters in convolutional neural networks?

Usually, when convolving images, the elements in the filter sum to one. Is this criterion enforced in convolutional neural networks? If yes, how?
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1answer
72 views

Anomaly classification probability on Machine Learning

I am using features to predict a dataset classification. I have use the Gradient Boosting Classifier of scikit-learn for the prediction and tune it to reduce the error classification. The error ...
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0answers
39 views

ML classification problem for matrix and distribution estimate for each cell in the matrix

I am trying to think about a machine learning/statistical learning related problem. But would love to get idea from people in the forum about related problem/work/resource. So, the problem idea is ...
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1answer
68 views

How to convert the objective function to canonic form of sparse coding?

As we know the conventional sparse coding problem (LASSO) is: $\min_{\alpha} \| X-D\alpha\|_F^2 + \lambda \|\alpha\|_{1} \tag{1}$ where $X$ , $D$, and $\alpha$ are data, dictionary and coefficients ...
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1answer
319 views

How to validate sentiment classification and compare different algorithms

I need to compare SVM and NB about sentiment classification by evaluating accuracy, precision and recall measures. I have 1500 manually classified documents, and I would know which is the best way to ...
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1answer
440 views

Test Error less than cross-validation error-implications?

If the test-set RMSE error of a model is less than cross-validated RMSE error, how can I interpret this? Is this abnormal? Does it imply a mistake in the methodology?
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1answer
782 views

Combining several variables into one outcome score: How is it done in the machine learning community?

I have got 8 cognitive (continuous) behaviour variables and would like to combine them into a composite score. I would then like to find the best predictors of this outcome (from about 50 predictors). ...
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158 views

What algorithm should be used for intelligent route planning system based on drivers experience

I am new here and I'm a student, my project is on machine learning for an intelligent route planning algorithm. Basically the summary of my project is to use a machine learning algorithm and ...
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1answer
274 views

Does PCA mean selecting most important features and ignoring the others?

Principal component analysis (PCA) is used to reduce the dimensions in our data set. While explaining PCA, they say that they are projecting the data to where there is huge variance; is that the same ...
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1k views

What is the definition of generalization error and its justification?

I was trying to understand rigorously what the goal of machine learning is. One could frame that one of the central goals of machine learning is to obtain the best possible function ever. But what ...
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82 views

measure the quality of feature vectors in terms of AUC and training time

I have computed 10 features for each example. I did an experiment to figure out which combinations of features can give the best classifier performance. I'm using libSVM for training. I noticed if I ...