Questions tagged [machine-learning]

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

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1answer
213 views

Convolution operator yields negative index of matrix

When I read about convolutional neural network from the internet, like this one, mostly I found that discrete convolution operator is defined as follow: $$C=I*F$$ $$C(x,y)={\sum_{a=0}^{k-1} }{\sum_{b=...
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1answer
85 views

How to train neural network that has different kind of layers

If we have MLP then we can easily compute the gradient for each parameters, by computing the gradient recursively begin with the last layer of the network, but suppose I have neural network that ...
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1answer
293 views

Directly proportional Trend in training and cross validation curves

In continuation with a question already asked, I tried the same curve on a different dataset I found. My model is a simple Logistic regression curve with OnevsRest Classifier. But the graph I obtained ...
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1answer
1k views

Training and cross validation error curves

I have a graph which plots training datasize on X axis and accuracy on y axis. I plotted the curves using sklearn's learning_curve. It is observed that the accuracy of training dataset decreases but ...
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2answers
5k views

What does “zero-meaned vector” mean

I'm trying to reproduce an algorithm designed in a paper. And everything is going well except one thing: It says ...
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1answer
49 views

Suggestions for good data science certified online courses [closed]

I am wondering if someone here can recommend some good data science certified online courses. A simple google research brings hundreds of online academy and I am lost. It is been one year since I am ...
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6answers
19k views

What is the difference between model hyperparameters and model parameters?

I have noticed that such terms as model hyperparameter and model parameter have been used interchangeably on the web without prior clarification. I think this is incorrect and needs explanation. ...
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1answer
864 views

Can I use categorical data and Decision Trees to regress a continuous variable?

Is there a way to take a set of data that consists of discrete values and predict a continuous value? Take for instance data that looks like: ...
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2answers
7k views

Does dataset training and test size affect algorithm?

I am dealing with a dataset that has a total of 81 records. Out of them I divided it to 54 records for the training and the rest for testing. I noticed a few things: Accuracy is low for given test ...
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1answer
1k views

Online Variational Autoencoder

when training a VAE, typically one samples from the latent distribution using the reparametrization trick using a fairly large minibatch size (>100) in the decoder/generator half of the VAE. I'm ...
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1answer
4k views

Cluster tendency using Hopkins statistic implementation in Python

The Hopkins statistic, is a statistic which gives a value which indicates the cluster tendency, in other words: how well the data can be clustered. If the value is between {0.01, ...,0.3}, the data ...
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1answer
1k views

Labeling Dataset Algorithmically

I am working in emotion analysis of tweets. I collected close to .6 million tweets. I dont want to label them manually, instead i coded a bunch of complex rules to arrive at their label. Before I ...
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0answers
68 views

Right choice of accuracy metric or loss function

I am developing a predictive model in sports vertical. As the game will progress, my model will predict the winning probability of each team playing. The problem I am facing is to what metric would ...
2
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1answer
376 views

model with only positive responses

Could any one help me know about different approaches, methods or algorithms to build a model only with positive responses. Let's assume we have a set of customers with a 'positive' behaviour. We ...
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2answers
1k views

Storing large data sets for python machine learning algorithm consumption

I'm reading up on how to clean/munge/wrangle data sets in order to run machine learning algorithms on them. Lots of info on how to do the actual wrangling, but a practical detail seems to be glossed ...
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3answers
2k views

Predict the best time of call

I have a dataset including a set of customers in different cities of California, time of calling for each customer, and the status of call (True if customer answers the call and False if customer does ...
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1answer
6k views

Linear regression - LMS with gradient descent vs normal equations

I wonder when to use linear regression with stochastic or batch gradient descent to minimize the cost function vs when to use normal equations? The algorithms using gradient descent are iterative, so ...
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1answer
249 views

Do logistic regression and softmax regression do the same thing?

If the both do the same thing then which give us better accuracy?
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5answers
2k views

Predictive modeling on big data set that can't fit into memory

I am trying to build a Decision-Tree model on top of a dataset that is about 10G in size on my local computer. However, I only have 8G memory. What I am doing now is just random sampling certain ...
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2answers
796 views

Binary classification: best ways to pre-procees the data

About the dataset I have a training dataset of 129 columns(last column being the classes, i.e., y values) 6068 rows I have to train some algo to do binary classification. The data set has 701 ...
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0answers
75 views

GPU Utilisation Issues

I observed that my GPU's memory is being consumed but the Utilisation stays 0. Because of this, my model is taking forever to load. I have tweaked this code to handle multilabel data. The only changes ...
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2answers
338 views

Is there any technique, which can decide no. of bags for Bagged Logistic regression?

In case of Bagged Logistic regression, people suggest more the bags better will be results. There should be some threshold for more. Is there any technique available which can suggest no. of bags for ...
2
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1answer
492 views

Cross validation techniques

What are the advantages vs disadvantages of cross validation types? Like k-fold, leave one out, etc.
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6answers
8k views

tool to label images for classification

Can anyone recommend a tool to quickly label several hundred images as an input for classification? I have ~500 microscopy images of cells. I want to assign categories such as 'healthy', 'dead', 'sick'...
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0answers
67 views

Parallel processing for feature selection in microarray dataset

I want to apply feature selection on a dataset with some 30-40K columns and 100 rows ( total size: 400MB-800MB ). To decrease the time consumed for calculations involved (feature-feature), I want to ...
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2answers
3k views

What is the purpose of multiple neurons in a hidden layer?

On the surface, this sounds like a pretty stupid question. However, i've spent the day poking around various sources and can't find an answer. Let me make the question more clear. Take this ...
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3answers
6k views

importing csv data in python

I have a csv file with around 130 columns and 6000 rows what is the best way to import them into python, so that I can later use them in a classification algorithm(columns are the labels and rows are ...
2
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1answer
633 views

Feature Selection, Machine learning and Time Series analysis, for large financial timeseries

I have m( around O(millions) ) of rows of type timestamp | val | ind1 | ind2 | ind3 | .... k entries My task is to predict the value of "val" for any future ...
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3answers
4k views

How to deal with a skewed data-set having all the samples almost similar?

I have a very large skewed training set where every feature's data-points are very similar ? For example, following is some ...
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0answers
150 views

Chance Curve in Accuracy-vs-Rank Plots in matlab

I'm working on an image classification problem where each test image (query image) is compared with a set of candidate images (of which several images are considered as "correct answers" or "relevant")...
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1answer
58 views

Picking training data

Suppose i want to have 80% training data and 20% testing data. How do i choose which 80% of the data to use for training? Should it be completely random? Like what if there is a class label with 2 ...
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2answers
1k views

Can overfitting occur in Advanced Optimization algorithms?

while taking an online course on machine learning by Andrew Ng on coursera, I came across a topic called overfitting. I know it can occur when gradient descent is used in linear or logistic regression ...
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2answers
2k views

Using Discretization from Training Set on Test Set in R

I am currently discretizing my training set in R with discretize from the bnlearn package. library(bnlearn) discretize(train, method = "quantile", breaks = 2) ...
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0answers
94 views

What algorithgm Android's ActivityRecognitionAPI uses?

I am curious to find out what is the algorithm behind Google's ActivityRecognitionAPI on the Android platform to find out what is the current state of the user (e.g., i the user us walking, running or ...
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3answers
9k views

How to choose a classifier after cross-validation?

When we do k-fold cross validation, should we just use the classifier that has the highest test accuracy? What is generally the best approach in getting a classifier from cross validation?
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2answers
5k views

Features of word vectors in word2vec

I am trying to do sentiment analysis. In order to convert the words to word vectors I am using word2vec model. Suppose I have all the sentences in a list named 'sentences' and I am passing these ...
2
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3answers
537 views

Technology stack for linear regression on (not so) large dataset

While attending to the Coursera's Machine Learning Course, I figured out that I could use a database from the company I work for (~50MM records) to do some linear regression experiments. But one of ...
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2answers
1k views

Machine Learning Best Practices for Big Dataset

I am about to graduate from my Master and had learnt about machine learning as well as performed research projects with it. I wonder about the best practices in the industry when performing machine ...
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3answers
41k views

How to get predictions with predict_generator on streaming test data in Keras?

In the Keras blog on training convnets from scratch, the code shows only the network running on training and validation data. What about test data? Is the validation data the same as test data (I ...
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1answer
442 views

Why Logistic regression into Spark Mllib does not use Maximum likelihood estimation? [duplicate]

During comparison estimates/ coefficients in 'R'& Spark Mllib of Logistic regression, It has been observed that estimates are not same. On further investigation, I found that R & Mllib has ...
2
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1answer
43 views

ML on dataset with heavy dependency on prefix

I have a target function, which heavily depends on vector prefix: (1, 2, 0, 0, 1, 2, 4) -> A (1, 2, 0, 55, 1, 99, 1) -> A (1, 2, 124, 55, 1, 99, 71) -> A (1, 3, -5, 0, 1, 2, 4) -> B ...
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1answer
176 views

What is the best strategy to use on data with many classification labels?

In general, what sort of supervised algorithms and techniques should I use on data that has the following charactersitcs: 2 potential classification labels? 3-5 potential classification labels? 6-10 ...
1
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1answer
480 views

Machine Learning to Get X, Y Coordinates From Picture of Plot

I am currently on a project where we have people place sticky notes on a X-Y axis to plot their beliefs on certain topics. These sticky notes can be of different colors to reflect different levels of ...
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2answers
59 views

Clusters with bounded diamter

In my application, I want to have clusters whose diameters are bounded by some fixed number. Also, the number of clusters in the data is unknown and therefore the clusters must be discovered without a ...
1
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0answers
221 views

Scalable training/updating of many small LSTM models

My situation is that I have many thousands of devices which each have their own specific LSTM model for anomaly prediction. These devices behave wildly differently so I don't think there is any way to ...
1
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2answers
2k views

How to deal with situation where LSTM fails to learn (constantly makes the same incorrect prediction) [closed]

I am trying to use LSTM neural networks in order to make a song composer. Basically this is based of a text generator (tries to predict the next character after looking at a sequence of characters) ...
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1answer
2k views

Using scikit-learn FeatureHasher

I have a huge data set with one of the columns named 'mail_id'. The mail_id is given in a very creepy format as shown below: ...
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4answers
353 views

Discrepancy between training set and real-world data set: domain adaptation?

I have read in literature that in some cases the training set is not representative for a real-world dataset. However, I cannot seem to find a proper term describing this phenomenon; what is the ...
0
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3answers
2k views

How to train neural networks with large sized data sets?

I have a dataset size of ~500000 with input dimension 46. I am trying to use Pybrain to train the network but the training is extremely slow for the whole dataset. Using batches of 50000 data points, ...
0
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1answer
790 views

Machine Learning model to find items that are frequently bought together using Hadoop Spark

I need to do my master thesis under Big Data Analytics - Machine Learning subject. I was challenged to create a Market Basket Analysis project on retail industry. My dataset contains transactions of ...