All Questions

I trained and saved a model that should predict a sons hight based on his fathers height. I then saved the model to Pickle. I can now load the model and want to use it but unfortunately a second ...

I understand the mathematical formalism behind how neural networks work as a classifier or perform regression analysis. But I face difficulty to realize how they are such a great denoising instrument. ...

I am trying to match descriptions of text. I have made a shonky algorithm that works and produces a 'score' based on how well they matched based on full word matches and words immediately preceding/...

I have a binary outcome for an imported CSV file I am working with. I used the sklearn library to use the logistic model to gather predictions for my target value and also generate probabilities. ...

I am dealing with the feature in which only one category takes up about 90%, the instances of more than 30 other categories are sparse. Is it reasonable to remove this feature before building an ...

I would like to train a model that estimate the time a given shop would take to repair for a bike using the data below: shops.csv ...

I'm trying to calculate similarity between texts with various length. My current approach is following: Using Universal Sentence Encoder I convert text to a set of vectors. I average these vectors to ...

What I am doing: I am predicting product ratings using boosted trees (XGBoost) with a dataset in this format: What I want to do: I want to use SHAP TreeExplainer to interpret each prediction my ...

I am not a math expert but have a basic understanding of linear algebra,calculus and probability and understands the math behind backprop. Currently I am trying to learn about policy gradient ...

I have studied Generative Adversarial Network for some time and currently im looking into Synthetic Aparture Radar Images and simulated SAR images. The problem with simulated SAR images is that they ...

How can I check if a machine learning model is feasible on a given dataset? What techniques like EDA, correlation etc. can be used to judge if a model is possible i.e. data and predictor variables ...

When I manually stop a local background job (that is running a loop over many rstan analyses) on Rstudio, Rstudio/R treat the job as if it's failed (rather than ...

p-stable locality sensitive hashing function:$$h_{a,b}(v)=\lfloor{\frac{a\cdot v+b}{w}\rfloor}$$ a is a vector random choosed from normal distribution, a is uniformly choosed from $[0,w]$, v is a ...

I read the paper and I saw that the logistic trend is defined as below : $$ g(t) = \frac{C(t)}{1 + \exp{ -k(t) (t - m(t)) }} $$ Where $k$ and $m$ are respectively a growth rate and an offset parameter....

I am doing feature selection using Sklearn: Tree-based feature selection : RandomForestClassifier.feature_importances_ L2-based feature selection: LogisticRegression.coef_ Target variable is binary ...

I have a multi-class classification problem. It performs quite well but on the least represented classes it doesn't. Indeed, here is the distribution : And here are the classification results of my ...

Why SQL Server Full memory usage.? If I was Apply size limits then also cross size linit.

I am training a model with around 200 images and it usually takes around 12 hours or more to complete. My colleagues' work only takes about a hour and a half to train. I am using windows 10 and ...

model = Sequential() model.add(Dense(16, activation="selu")) model.add(Dense(1, activation="sigmoid")) I am using Keras to create a binary classifier. My data ...

Given a sample of data where the samples are taken over irregular intervals, what is the most sensible way of going about calculating the mean and Standard deviation? Specifically, suppose we are ...

As we all know Keras backend uses Tensorflow and so it should give out same kind of results when we provide same parameters, hyper-parameters, weights and biases initialisation at each layer, but ...

Suppose that I am performing Sequential Pattern Mining (maxgap = 1, i.e. rules for consecutive windows) and I ran the following code from arulesSequences in R Studio to determine significant rules ...

I am trying to develop an rl agent using DQN algorithm.During training, the agent interacts with environment which is a simulated one.Each episode takes around 10 mins to run. This way if want my ...

I'm quite new to data science and only slowly following the necessary steps to get valid results using scikit-learn. As far as I understand you fit and transform the training data and only transform ...

I have implemented a deep learning network : Conv -> Relu -> Maxpool -> flattens -> dense -> softmax. the network has 6178 parameters. I am trying to do gradient checking on my deep learning network. ...

When I tried to execute the below code for epoch in range(training_epochs): sess.run(training_step, feed_dict={x:train_x,y:train_y}) the following error is ...

I have data set that has data for patients: Arrival_Date : is when the patient has arrived Seen_By_Nurse : is number of minutes patient take to be seen by nurse since arrival when value is NaN it ...

I'm trying to code the design function used in linear regression using numpy and I get this error: Traceback (most recent call last): File "C:\Users\visha\AppData\Local\Continuum\anaconda3\lib\...

Background: I am in my last semester of electrical engineering, and I am working on my senior design project. The senior design project is a two-semester design project in which students outline, or ...

From what I've read normal skewed is a distribution that has all the properties of normal distribution and is skewed: according to this resource:https://www.statisticshowto.datasciencecentral.com/...

I want to use Prioritized Experience Replay for whole episodes, instead for single transitions. What's the best way to define the priorities as episodes can be of different lengths? Personally I can ...

I'm working on a machine learning class, and we're using supervised learning right now, starting with decision trees. I'm using the UCI Credit Card dataset (whether or not certain people will default ...

I'm working with several estimators of all kind. Then, I want to stack these estimators, and the best is if they have low correlation between them. I suppose that the correlation method depends on ...

Is there a standard term for a feature that always has the same value, i.e. that can be discarded without loss of information? For example I am trying to classify cats vs dogs, and every example in ...

Is there a more elegant way to write a code like this? ...

I would like to know the differences between: linearSVC() SVC(kernel='lineaer) ...

I'm trying to define the number of the repeated samples in sklearn random forest subsamples: Here is my code: ...

I am training a classifier (similar to logistic regression) on MNIST. I have 10 one -vs.-all classifiers for each number, each of which independently achieves >90% test set accuracy. However, when I ...

On the GLUE faq, they say: Similarly, for SST, the data provided is already tokenized. We're working on obtaining a version that is not tokenized. Feel free to train on other distributions of ...

For example, i need to generate circles. I have dataset of images with non-intersecting circles and can generate random circles with DCGAN, but each circle has a different diameter. So I need to ...

I am experimenting different loss functions for my regression model. I noticed that in the sklearn, there are: sklearn.linear_model.HuberRegressor and sklearn.linear_model.ElasticNet To me, both use ...

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Working on some voluminous data sets, I have been interested in methods for dimension reduction and plotting. I have stumbled upon this novel technique : UMAP (https://arxiv.org/pdf/1802.03426.pdf), ...

I am re-writing the H-Net code in Keras for cross-domain image similarity. The network architecture is described in the attached paper. I wrote the encoder and decoder parts but unable to get similar ...

Like in tensorflow I get accuracy for each step - ...

This question has been asked before, but never (that I can see) satisfactorily answered. I'm reading Youtube's paper on their recommender system. The system has two elements, the first of which is a ...

I've been doing a few DataScience competitions now, and i'm noticing something quite odd and frustrating to me. Why is it frustrating? Because , in theory, when you read about datascience it's all ...

I have been trying to apply Fourier transform for two days, but haven't been able to because all the examples I've seen so far are not on actual dataset and use standard values that I don't understand ...

We need to analyse a lot of articles relevant to political instability in a given country (things like the possibility of a coalition / a snap election etc). The problem is that I could not find any ...

Can anyone tell suggest the best practice for clustering data with mixtured features (both with categorical and continuous). I am struggling with a problem; I realized that for all metrics algorithms ...