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Published: 6/12/2016Here's the scenario, There's a database with thousands of singleoption questions for testing a specific skills, and a large number of users (either professional or amateur in this skill), each of whi ... Read moreSource: datascience.stackexchange.com


Published: 6/12/2016I'm trying to build a bayesian network for satisfcation survey data. My data is made of 13 questions about services, products etc... each customer can answer from 1 (Very unsatisfied) to 4 (very satis ... Read moreSource: datascience.stackexchange.com

Published: 6/12/2016There are several feature selection / variable selection approaches (see for example Guyon & Elisseeff, 2003 ; Liu et al., 2010 ): filter methods (e.g., correlationbased, entropybased, random fo ... Read moreSource: datascience.stackexchange.com

Published: 6/12/2016I'm currently working on implementing Stochastic Gradient Descent (SGD) for neural nets using backpropagation, and while I understand its purpose I have some questions about how to choose values for t ... Read moreSource: datascience.stackexchange.com

Published: 6/12/2016In the Amazon Go page they claim to use "deep learning". Where is deep learning used in the "Go" service? Is it computer vision or inventory management? Read moreSource: datascience.stackexchange.com

Published: 6/12/2016I built a CNN to learn to classify EEG data (only about 4000 training examples, 2 classes, 5050 class balance). Each training example is 64x512, with 5 channels each Ive tried to keep the network as ... Read moreSource: datascience.stackexchange.com

Published: 6/12/2016My question relates to the intuition behind clustering examples in a categorical space of binary variables. Assume for argument sake that we use kmeans clustering algorithm. In such a space the possi ... Read moreSource: datascience.stackexchange.com

Published: 6/12/2016so to be more clear lets consider the problem of loan default prediction. Let's say I have trained and tested offline multiple classifiers and ensembled them. Then I gave this model to production. Bu ... Read moreSource: datascience.stackexchange.com

Published: 6/12/2016here is a neural net I made. It doesn't work at all, and I would like to know if you could provide any explanation why. def sigmoid(x): sigOfX = (1/(1+np.exp(x))) return sigOfX class sinNeuralNet(obj ... Read moreSource: datascience.stackexchange.com

Published: 6/12/2016I'm trying to classify images into two classes. For this purpose, I implemented a CNN using Tensorflow, but for some reason, it does not converge. cnn(x) always produces ones. Here is my code, where l ... Read moreSource: datascience.stackexchange.com

Published: 6/12/2016In this article, we revisit the most fundamental statistics theorem, talking in layman terms. We investigate a special but interesting and useful case, that is not discussed in textbooks, data camps, ... Read moreSource: www.datasciencecentral.com

Published: 6/12/2016XGBoost $ cat test.txt 0 0:5 1:5 2:5 3:5 $ cat dump.raw.txt booster[0]: 0:[f1<33.925] yes=1,no=2,missing=1 1:[f3<192] yes=3,no=4,missing=3 3:leaf=1.73333 4:leaf=0.727273 2:leaf=1.99917 booste ... Read moreSource: datascience.stackexchange.com

Published: 6/12/2016Summary: AI and predictive analytics are now so prevalent in our daytoday lives that it has raised the attention of the government, particularly about how certain groups might be adversely impacted ... Read moreSource: www.datasciencecentral.com

Published: 6/12/2016Someone writes: On the website https://odajournal.com/ you find a lot of material for Optimal (or “optimizing”) Data Analysis (ODA) which is described as: In the Optimal (or “optimizing”) Data Analysi ... Read moreSource: andrewgelman.com

Published: 6/12/2016I am trying to run a logistic regression on a data set where my dependent variable is a proportion of a binary variable, rather than the binary variable itself. I have seen a ton of documentation that ... Read moreSource: datascience.stackexchange.com

Published: 5/12/2016I have a very large dataset consisting of approximately 15,000 rows of survey data. The surveys are quantitative summaries of interviews with investors regarding their rankings of financial asset mana ... Read moreSource: datascience.stackexchange.com

Published: 5/12/2016I have created Data frame to read csv file using sqlContext from which I need to convert a column of table to RDD and then dense Vector to perform matrix multiplication . I am finding it difficult to ... Read moreSource: datascience.stackexchange.com

Published: 5/12/2016I am a Python developer but I want to become a data scientist. My Question: At its core what is the bare minimum I need to have to make this transition? I know it cannot simply be that I need to learn ... Read moreSource: datascience.stackexchange.com

Published: 5/12/2016Jonathan Gilligan writes: I’m writing to let you know about a preprint that uses Stan in what I think is a novel manner: Two graduate students and I developed an agentbased simulation of a pred ... Read moreSource: andrewgelman.com

Published: 5/12/2016if I have a training data set and I'll train a Naive Bayes Classifier on it and I got an attribute value which has the probability zero. How to handle this if I later want to predict the classificatio ... Read moreSource: datascience.stackexchange.com

Published: 5/12/2016I have a DF weather_opinion "the weather is cold" "it's quite sunny today" "it's raining" "today the climate seems to be pleasant" "I feel dizzy today" And a list: list_tags = ["cold", "sunny" "rainin ... Read moreSource: datascience.stackexchange.com
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