Questions tagged [learning]
The learning tag has no usage guidance.
37
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Learning additional parameters that are not weights of a neural network
In addition to training the weights of a neural network, I also want to optimize other parameters (that are constant but satisfy some conditions over the entire data set). As an example, one can ...
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Image Classification | High loss
i am working on image classifiaction. With keras, tensorflow.
...
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Textrank to Extract importance sentences
I used text rank to extract the most important sentences from a set of tasks that some professions perform, but I don't know if it would be correct to just sum the textrank outputs to know the output ...
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Is R programming a good way to start with Data Science? [closed]
I am a software engineer (currently CTO) specialized on web and mobile applications picking up data science skills. I do this mainly for future projects within my startup that works in digital ...
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23
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Classification or Regression approach?
I have a dataset with x variables and the target y (between 0 and 100%, so 0 and 1)
My goal os to predict if a sample is in a group of y [0,0.25), [25,50) or [50,100].
And I am wondering if I should ...
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How to change/adapt loss function while using "class" incremental learning
As a beginner on class incremental learning and trying to understand the general concept. In class incremental learning, we have a model that can make a classification between classes A, B, and C. By ...
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r or r+1 in Temporal Difference Learning?
this is probably a very simple question for most of you but I have seen this different formulation of the TD Learning function in many different papers and can't really wrap my head around it:
Just as ...
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How to visualize ner dataset tagged using BILOU?
I have a dataset for ner which is tagged using BILOU tagging method and example of same is below
...
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Individual models gives quite same distribution on Test set, whereas Ensembling gives better result but very different distribution
I am working on a binary classification problem with unbalanced data (17% for positive class).
The problem is as following:
My three individual models when predicting on the test set (for which I don'...
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1
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45
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using average precision as metric for imbalanced problem (learning curve example) [closed]
I have an imbalanced problem (2% target class) and therefore need an appropriate metric - so I chose average_precision.
My code:
...
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1
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114
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How to approach for predicting semantic similarity between two phrases
I need pointers on the latest research, tools, and techniques for predicting semantic similarity between two phrases.
Problem Statement: Given two propositions A ...
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Response variable at the group level, independent variables at the entity level
I have a dataset of entities which each belong to a particular group (i.e. entity=schools and group=school district). I also have lots of auxiliary variables on each entity.
However, for my response ...
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Tableau: Dealing with Date values [closed]
Im a noob at tableau. I have a quick question
I have data that doesn't explicitly list the date. (There is no column labelled "date" )
However there are columns with the following headers:
"Income ...
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288
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Colab can not connect to GPU from a python file [closed]
I am trying to run a github deep learning repository in Colab but I can not connect the python files to colab GPU.
I can connect to GPU when writing a script in the colab notebook e.g. when I run ...
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398
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Knowing Joint probability distribution between feature-label space
I am doing a course CORNELL CS4780 "Machine Learning for Intelligent Systems". you can find the link here for the one I am going to refer 1st lecture
The professor explains, we have a sample
$D ={...
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How to use learning curve in reality
CONTEXT:
I have some simulated data by which I made and trained a model. during my training, I enjoyed having a large number of samples, and therefore my model is leveraging it by being decently ...
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Sklearn Decision Tree as weak learner in Adaboost not working properly
I'm trying to implement Adaboost algorithm with sklearn decision tree as the Weak Learner - at each step I want to choose one feature with one threshold to classify all samples.
I have 1400 long ...
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How to explain the connection between the input layer and H1 of this CNN Architecture?
I am currently reading the paper proposed by LeCun et al. for handwritten zip code recognition. There is this figure below visualizing the CNN architecture. But I do not really understand how the ...
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What Non-linearities are best in Denoising RNN Autoencoders and where should the go?
I’m employing a denoising RNN autoencoder for a project relating to motion capture data. This is my first time using auto encoder architectures and I was just wondering what non-linearities should be ...
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154
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A generalized quadratic loss for deep neural network for multi-class classification
I'm evaluating the possibility to introduce a new loss for the subject described above.
Let $l$ be the number of examples, $q$ the number of classes,
$p_{i,r}$ the $r$ classifier output on example $i$...
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1
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170
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Growth function of a 6-dimensional linear classifier
In our course, we are dealing with a d-dimensional classification problem
($\chi = \mathbb{R}^{d}$ as our input space, and $y = \{-1,+1\}$). Our hypothesis class $H$ consists of all hypotheses of the ...
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118
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Learning to rank: how is the label calculated?
I am studying learning to rank and not sure I understand how the train sample and final label (relevance score) is constructed.
Lets assume we sell furniture online. We have logged customer's query, ...
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489
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Linear Regression
I'm starting to learn machine learning and one of the first things that is mentioned is the usage of a linear regression method. Basically, we have a bunch of data points and we want to fit a line ...
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How do I approach learning Data Science/ML the 'rightest' way? [closed]
First of all, I am not sure if this is the right place to post this so please do let me know if it isn't and tell me where it should be. I really just don't know where to go with this question.
Some ...
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Which machine learning algorithm can be used for traffic prediction using images from Google Maps? [closed]
I am doing a traffic prediction project.
I am using data from Google Maps. I'm collecting maps of different location and analyzing them. I am converting the maps to images, analyzing the image, and ...
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275
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CNN to many outputs
I have a dataset with 100 columns (categorial one-hot encoded) and 1 column with text data (simple sentences) and i want to build a neural network to arround 380.000 outputs labels. I have no idea ...
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896
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Why can't continuous variables be used for the estimator of learning curves, when using StratifiedKFold to split the dataset?
I want to produce learning curves for three regression models run on data containing 200 samples, 10 features and 1 target variable.
The target variable contains two clusters/peaks, making it ...
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4
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565
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How to know for sure if we can learn from a given data or not?
I want to know that given a set of data and a target, how we can know for sure whether we can learn from that data to make any inference or not?
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Machine Learning/Text Analysis/Algorithm Pointers
I'm looking for a reference or point in the right direction since I'm not too familiar with machine learning or algorithms. I'd prefer to work in R, but I could also do Python. Any reference to a ...
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Columns with no (or nearly no) differences between rows worth keeping?
I have a dataset which contains multiple columns. On analysis, I found out that there were few columns which contain just a single value. There was 0 in all the rows of these columns. Does it hold any ...
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Learning to cluster using one sample per class
I have a question regarding an idea. I know many ML algorithms and I know how they work and perform. But I have an idea which I believe in should be similar to one of the current available methods.
...
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3
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How to prepare data for LSTM time series prediction
I have a binary classification task for time series data.
Every 14 rows in my CSV is relevant to one time slot. How should I prepare this data to be used in LSTM? In other word how to feed the model ...
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Which is better for Data Science, a double major in Math & CS or Physics & CS? [closed]
My dream occupation is to work as a Data Scientist.
I'm soon going to be completing my first semester as a physics student, as part of an incredibly prestigious physics program. We get to run an ...
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Topics to cover for software developer interested in data analytics
First of all I don't know if this is the appropriate place to post this question. If it's not, I apologize in advance. It seems like the most relevant Stack Exchange sub.
A little about myself:
I'm ...
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Any guidance for new beginners interested in data science [closed]
I am a student with a master degree in biostatistics. I am interested in data science. I know SAS and R. No experience with python. May I ask for your experts' advice on how to teach myself data ...
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174
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Verification of trained system
I have trained a system in order to detect some features from a set of scenarios. Now the system can detect and classify that set. How can I validate how that system works in real world? What ...
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Interpret User Interfaces with Machine Learning
I am currently working on a prototype of an application that should be able to interact with user interfaces.
Now every user interface has some common elements, like buttons, scrollbars, input fields ...
