# Tagged Questions

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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### Mortgage loan predictive analysis

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