Questions tagged [machine-learning]

Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervised learning, etc. ALWAYS ADD A MORE SPECIFIC TAG.

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831 views

How should I use Recurrent Neural Network to model this problem? [closed]

I am using Keras to do a machine learning task: Let's say I want to predict the time that a user spends on a product page. Each training case is a partial user visit session. One single user may ...
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1answer
450 views

Using trees after variable selection using Lasso/Random

I am new into Machine Learning so please excuse me if my question is naive. My question is, is it possible to use trees for example rpart or ctree after variable selection procedures such as Lasso/...
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187 views

Tuning priors/weights/costs to counteract class imbalance

I have a classification problem which consists of two classes. It has high class imbalance. There are around 85% data points for the negative class and only 15% for the positive class. One option is ...
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1answer
347 views

Representation input and output nodes in neural network for $\textit{AlphaZero}$ chess?

I am wondering how the neural network for AlphaZero chess works. I know that it takes a historic set of states of the board as input nodes. But I am wondering how many output nodes there are and what ...
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1answer
454 views

What characteristics should the input data have for a neural network?

I am planning to use a neural network for prediction. For example, to predict whether a student will pass a course based on his previous academic records or characteristics. I was wondering how to ...
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1answer
182 views

Retrain random forest with important variables

So I have a classification problem with around 2000 predictors. First I run a random forest model to get important variables. Then I only use those variables (let say the top 30) to run the model ...
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1answer
16 views

How to rank data based on cross-validation

I had this problem from a long time. I have small dataset with about 1000 data points. The data is labeled as 1 or 0 (i.e. ...
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0answers
43 views

How to use random forest for regression after it is trained

I don't understand how to work with a random forest regressor after it is trained. I read and coded some tutorials about regression with random forests in Python with scikit but I don't understand how ...
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1answer
180 views

Recommendations for textbooks covering current data mining/machine learning techniques for fraud detection?

I work in the health insurance field, but a general treatment of fraud detection methodologies would still be helpful. So far I've discovered brief articles outlining particular techniques used in ...
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1answer
259 views

Misunderstanding of E-Greedy Monte Carlo Proof

I'm confused about one step of the e-greedy Monte Carlo control proof on page 83 of Sutton and Barto Reinforcement Learning. The book annotates saying "(the sum is a weighted average with ...
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1answer
298 views

Question about implementing nested Chinese Restaurant Process (nCRP)

I am trying to follow the original paper on nCRP by Blei et al., 2010 and am confused with it's implementation. The authors describe the analogy for an nCRP as follows: A tourist arrives at the ...
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1answer
2k views

out of bag error in random forest and data partitioning

I have a question concerning OOB error in random forests and data partitioning. As far as i know in random forests the trees are not pruned. Also we use OOB error for measuring the performance of the ...
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1answer
558 views

Should I use the same weight initialization for each fold in cross validation?

Say, for example, I have 5 splits of my data. Can I randomly initialize the weights for my neural network at the start of each split? Or should I save the initial weights randomly initialized for the ...
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2answers
1k views

Random forest and ridge regression

Can we apply the concept of ridge regression in random forest for predicting the values in order to get more accurate results? Random forest using regression trees for the prediction. When there is a ...
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2answers
768 views

Variational inference: how to rewrite ELBO?

I am reading this paper on variational inference and this website. One thing I am confused about is how they get to decompose ELBO, where $ELBO(q) = E_q[log~p(z,x)] - E_q[log~q(z)]$, when focusing ...
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1answer
87 views

Understanding linear regression

In class we've seen that $a$ (the weights) must satisfy $$X^T (y-Xa) =0$$ Here $X$ is a $(n\times d)$ matrix (so we have $n$ samples in $\mathbb R^d$) let's denote the residuals $r = y-Xa$. In our ...
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1answer
165 views

Interpreting GLM regression analysis result

I'm using the following code in R to predict votes (e.g. non-negative integer count data). ...
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1answer
714 views

How to build ROC curve (or AUC) of classification model from confusion matrix only

I've been looking into using ROC curves as a evaluation tool of a multi-class classification. The only data I have about this classification is in form of 7-by-7 confusion matrix. Visualisation of ...
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2answers
156 views

Regression on Predicting Time

If I have a dataset like this: ...
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2answers
867 views

Confidence Interval - Binary classification [duplicate]

How do we calculate a confidence interval for a result in binary classifiers ? CI for regression problems makes sense since we have a variable estimated output that I can calculate its estimated mean ...
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1answer
96 views

Doubts on Hypothesis set?

Newbie to ML, i am having a hard time understanding what exactly is a hypothesis set. From what i understand: In Supervised Learning, we will be given Input, Output. We need to find a Hypothesis ...
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1answer
1k views

Pre-processing (center, scale, impute) among training sets (different forms) and the test set - what is a good approach?

I am currently working on a multi-class classification problem with a large training set. However, it has some specific characteristics, which induced me to experiment with it, resulting in few ...
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0answers
436 views

How to choose the right step size for alpha in the elastic net?

I'm using "glmnet" package in R to learn different elastic net regressions. As you know, elastic net should perform at least as good as LASSO regression. But it's not the case for me and LASSO perform ...
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640 views

How to represent outliers for multi dimensional data (local outlier factor)

Below graph taken from http://en.wikipedia.org/wiki/Local_outlier_factor displays "LOF scores : LOF image : This is great for two dimensional data but what about data > than two dimensions. How ...
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2answers
532 views

Xgboost Feature Importance shift

If I plot the feature importance of my xgboost model I get for example f10,f3,f7,f99,... as the most important features. Now I decided to remove f3 and I imagined the new feature importance would be ...
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1answer
143 views

Changeing the hypothesis while generating samples

I'm currently reading / working through: Learning from Data: A short course by Abu-Mostafa et. al to familiarize my self with the shift in language from Stats to ML. In the section on feasibility we ...
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276 views

Regression or time series model to predict trend

DATA I have the following data at hand: data about internet usage, per hour, per user, per part of the day (morning, afternoon, evening); the category of websites visited and their duration; ...
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3answers
492 views

Which is the best classifier and with what performance measures?

I tried to implement a Classifier comparison like in the scikit-learn for text classification. I used an 81 instances as a training sample and a 46 instances as a test sample. I tried several ...
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2answers
73 views

Multi-View Survival Analysis

I have a data set containing various subsets of medical data about a cohort of patients. For example there are blood test results, demographics, medical examination results and a medical history among ...
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0answers
215 views

Spearman rho statistical significance value (z)

How can I calculate the statistical significance (Z) of spearman's footrule rho? I came across the formula at this wiki page ...
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2answers
364 views

Using ML approaches to build a recommender engine for sales team

I work at a startup as a developer, but I wanted to help out our sales team with running some ML algorithms on the data. A bit of context: Most of our revenue comes from ad purchases, so in a nutshell,...
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1answer
592 views

what is the correct formula of momentum for gradient descent?

I have been trying to get a better understanding of momentum, but in my search for clarification I got pretty confused. The main reason is that there seem to be multiple different, non-equivalent ...
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0answers
405 views

Which model is better based on test and training accuracy

I have this assignment question: You are given a dataset for cancer detection having two classes (binary classification). 0 stands for “cancer not detected” and 1 for “cancer detected”. This ...
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1answer
920 views

XGBoost tree “Value” output: [duplicate]

Using the following R code I obtain a decision tree using the agaricus dataset: ...
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1answer
103 views

Linear Regression and High Dimensional Categorical Data

I've read that mean encoding is useful for classification tasks with high dimensional categorical data. My question: What kinds of encodings are effective for high dimensional categorical data in ...
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1answer
693 views

Comparability of the negative log marginal likelihood in Gaussian processes

I have a given data set $\mathcal{X}$ with features $X$ and targets $Y$ that I learn with a Gaussian process regression, kernelized by $k$. Now I produce a new set of features $X^{\prime}$ (which ...
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2answers
1k views

Rescaling input features for neural networks regression

In Neural Nets for the regression problem, we rescale the continuous labels consistently with the output activation function, i.e. normalize them if the logistic sigmoid is used, or adjusted normalize ...
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1answer
668 views

Cross validation accuracy is the same as the fraction of negative labels - what does it mean?

I have a dataset for classification (binary - 1/0) that has around 4000 samples that I use to train the model (I'm using an SVM, if that's relevant). To check whether everything is working fine, I ...
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1answer
40 views

Decomposition of vector into product of a function on a matrix and a function on a vector - Possible? [closed]

Say I have access to $N$-dim vector $Y$, $N \times p$ matrix $X$, and $q$-dim vector $Z$. Ultimately, I would like to learn the functions $g,f$ in: $\underset{N\times1}{\underbrace{Y}}=\underset{N\...
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1answer
660 views

Find covariance if given mean and variance

I have a signal x that I want to classify in one of the classes A and B in which the means are Ma=[0.5,0.6] and Mb=[2,2] and with variances ...
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0answers
83 views

Which ML algorithm is suitable for the following problem?

Assume i have x states each defined by an n-dimensional feature vector. In addition i have a set of actions which can be taken in each state resulting in a state action score. What would be an ...
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0answers
66 views

How to sample weights for weighted kernels?

I'm using a SVM classifier with a weighted RBF kernel. My dataset has 17 features. In the RBF kernel I will use a weight for each feature. Of course the weights must sum to one. For choosing the best ...
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1answer
2k views

How does regularization work for a Gaussian Process classification model?

I'm a bit confused about Gaussian Process models for classification. In chapter 3 of http://www.gaussianprocess.org/gpml/ it is claimed that you can use a logit or probit model without any additional ...
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2answers
34 views

What does the “probability of a dataset” refer to?

I am studying Machine Learning in the Bioshop, 2006 textbook. Often he talks about the "probability of a dataset". I can't understand what he is referring to; in my mind, a dataset is not a possible ...
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1answer
61 views

What is the reasons for a model to have a high cross validation score and yet underperforms on unseen data?

I have a model that is based on an experiment collected on 100 subjects. We are testing the model as follows: Record raw data from the subjects For each subject, compute the feature from the raw data ...
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3answers
82 views

How can I understand the concept of a noise in machine learning?

In Bishop's book, one of the first examples is shown here Essentially, the data $x$ are randomly generated, and $t$ are generated by running $x$ through a function $\sin(2\pi x)$, then Gaussian ...
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2answers
182 views

step by step tutorial for newbie

I'm looking to join the field of statistics and more exactly to forecasting. I'm a software developer and I just started playing with R. Can you recommend me some tutorials related to forecasting, ...
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1answer
90 views

Why the dot product of two vectors in sklearn is not a scalar? [closed]

In a 2d Euclidean space, Let point $a=(a_x, a_y)=(1,1)$; Let point $b=(b_x, b_y)=(5,1)$; Let point $c=(c_x, c_y)=(4,4)$; the squared Euclidean distance between point a and point b is equal to $(...
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1answer
295 views

Does Matching Pursuit and Soft Thresholding return the same minimizer?

I wanted to understand if the solutions (minimizers) obtained by Matching Pursuit algorithms (say Basis Pursuit denoising) and Soft Thresholding yielded the same minimizer (same solution or same ...
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1answer
83 views

Predicting Which Users will Login at a particular time

I have a challenging use case at work. We have logs of which user login at which times. So, consider 7 days a week, 24 hours. We have to map these 7x24 slots to different users. I am trying to ...