Questions tagged [sparse]
The sparse tag has no usage guidance.
22
questions
1
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0answers
10 views
Suggestions for binary time-series-classification model for small dataset
Hopefully I´m at the right place for my question:
I´m looking for suggestions for models to use to classify multivariate time series. I´m trying to find a way of classifying the behaviour of motors ...
2
votes
1answer
68 views
Best metric and hyperparameters in dimension reduction with UMAP for binary sparse data
I am playing with a dimensionality reduction step prior to clustering for a pretty large sparse binary matrix of almost 3000 columns and 50k rows.
My idea is to embed the 3000 dimensions into a two-...
1
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0answers
27 views
Linear regression on sparse matrix?
I have a matrix with sparse data. A small extract from it is seen below. The columns represent years and the rows represent different race tracks. The feature values are velocities on that specific ...
0
votes
1answer
70 views
Dictionary learning for image classification
I'm wondering if the approach I'm thinking of could even work.
I want to use dictionary learning for image classification. The first step would be to learn the dictionary from a set of similar yet ...
1
vote
1answer
171 views
Predicting high frequency sparse time series data in python
I have a dataset of a couple of EV charging stations (10 min frequency) over 1 year. This data consists of lots of 0's, since there is no continuous flow of cars coming to charge but rather ...
1
vote
3answers
523 views
How to create a big data frame in Python
I have a sparse matrix, $X$, created by TfidfVectorizer and its size is $(500000, 200000)$. I want to convert $X$ to a data frame but I'm always getting a memory error.
I tried
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1
vote
1answer
49 views
Predicting sparse time series data
I have a dataset of a couple of EV charging stations (10 min frequency) over 1 year. This data consists of lots of 0s, since there is no continuous flow of cars coming to charge, but rather ...
0
votes
1answer
58 views
How to work with input which is a combination of metadata+ vectorized text data + image pixel data to build a Regression Model (predict views)?
There are 4 datasets (all in csv format), each has a uniqueID column by which each record can be identified. Image and text datasets are dense datasets.(need to be converted to ndarray).
Can someone ...
2
votes
1answer
222 views
Why do my target labels need to begin at 0 for sparse categorical cross entropy to work?
I'm following a guide here to implement image segmentation in Keras.
One thing I'm confused about are these lines:
...
1
vote
1answer
75 views
Anomaly detection on sparse categorical data
I have a big dataset with a column "clientid" and a categorical column "choice".
I want to find out what are the clients that have strange combinations of choices (less frequent ...
0
votes
0answers
10 views
Correlation coefficient for weighted value pairs
I want to obtain an appropriate correlation statistic for sparse matrices, in two different cases.
Case 1
A small rectangular matrix (size: 3-20 elements long or wide) with a single value per row, per ...
0
votes
1answer
40 views
Correlation/distance between sparse vectors
I am looking for a metric for comparing gene count tables. These are long columns of data (a few millions genes by a few dozen samples), with all non-negative entries, about 90% of which are zeros. ...
1
vote
1answer
366 views
unsupervised anomaly detection on sparse data
Given that I have a very sparse data matrix with continuous features, like this dataframe for example
...
0
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1answer
142 views
Softmax regression cost function code [closed]
I really do not understand what does this code do
M = sparse.coo_matrix(([1]*n, (Y, range(n))), shape=(k,n)).toarray()
The code is related to calculating the ...
1
vote
0answers
13 views
Autoencoder for Extremely Sparse Data
I am attempting to train an autoencoder on data that is extremely sparse. Each datapoint is only zeros and ones and contains ~3% 1s. Being that the data is mostly zero the autoencoder learns to ...
1
vote
0answers
26 views
Classifying sparse binary data for int value
I'm very new to data science and still trying to get the grips. The problem I'm trying to tackle is, we have a pool of footballers from a league and data objects representing a group of 11 footballers ...
1
vote
0answers
19 views
Sparse Covariance Selection
I was reading this article https://www.di.ens.fr/~aspremon/PDF/CovSelSIMAX.pdf, whose goal is to estimate the covariance matrix from a the sample covariance matrix drawn from a distribution $X$.
' ...
1
vote
0answers
40 views
Custom Loss Function for Mixing Sparse and Dense Features for a Prediction Problem
I have a largely uncorrelated feature space of about 40 dichotomous features, using which I'm trying to predict a continuous target variable.
Now, some of these features are very sparse (Active less ...
3
votes
0answers
1k views
Converting pandas dataframe to scipy sparse arrays
Converting pandas data frame with mixed column types -- numerical, ordinal as well as categorical -- to Scipy sparse arrays is a central problem in machine learning.
Now, if my pandas' data frame ...
0
votes
1answer
217 views
What are the sparse and dense vector ? I cant undestand ,can you explain to me?please.Why do we use for?
I am new to neural networks, embeddings, etc. I am struggling understanding things like sparse representation, embeddings, and especially sparse vectors. Could you explain these to me? Why do we need ...
2
votes
1answer
972 views
Convert Pandas Dataframe with mixed datatypes to LibSVM format
I have a pandas data frame with about Million rows and 3 columns. The columns are of 3 different datatypes. NumberOfFollowers is of a numerical datatype, UserName is of a categorical data type, ...
1
vote
0answers
185 views
Scipy Sparse vstack memory error
I have a bunch of scipy matrices (of the same #columns) loaded from disk.
I want to combine them into one scipy sparse matrix.
I am using scipy sparse vstack method.
I am able to load the ...
