Questions tagged [data-science-model]

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Difference between Granger causality and VAR(1)?

For my VAR(1) I get that the causal variable in each equation is statistically significant at 10%. But for Granger causality at 10% I only get that 1 variable granger causes the other and not the ...
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Calculating optimal number of topics for topic modeling (LDA)

am going to do topic modeling via LDA. I run my commands to see the optimal number of topics. The output was as follows: It is a bit different from any other plots that I have ever seen. Do you think ...
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Grid Search returns only NaNs. Is it my data? Is it my application? [closed]

I am attempting to optimize parameters using GridSearchCV . However, when I do so the gridsearch appears to run, then returns all NaN values. I read somewhere that this means the model is failing to ...
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1answer
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Classification Based Collaborative Filtering Model

I was going through algorithms for collaborative filtering-based prediction. Most of the places, I read about using matrix factorization based on ratings of the likeness of the user. But for my use ...
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1answer
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What is the architecture of PoseNet?

PoseNet is state of art approach and I am using it for a pose estimation. I read on the internet that pose net uses models like MobileNet or VGG etc. I would like to know that is PoseNet itself a ...
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1answer
24 views

Prediction Algorithm for Data with high Randomness

I have data for the orders of the previous year containing the product and the seller who sold the product. I have an information product, product category, seller, delivery address price etc. ...
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Predicting the test data with LinearRegression model gives ValueError: shapes (8523,1606) and (1605,) not aligned: 1606 (dim 1) != 1605 (dim 0)

Fitting the model, testing and getting the score or r2 does not give the error. But when I try to predict the actual data I get this ValueError: ...
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1answer
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Binary Cross Entropy | Manual scalars [closed]

I am wanting to make print statements "showing my working out" of Binary Cross Entropy loss function, that works with ...
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1answer
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Can Boosting and Bagging be applied to heterogeneous algorithms?

Stacking can be achieved with heterogeneous algorithms such as RF, SVM and KNN. However, can such heterogeneously be achieved in Bagging or Boosting? For example, in Boosting, instead of using RF in ...
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Keras Reproducibility Problem on Jupyter notebook

I developed a model with Keras. However, every time I run the model from the beginning, I get different score values. I typed the code below to provide "reproducibility" but unfortunately, I'...
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Hypothesis about Telecom Data Analysis - a Q from new learner

in one of my online courses, I'm supposed to analyze and plot any problem of my choice, cool right! Accordingly, I have the data from one Internet Service Provider (ISP) which is related to the ...
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1answer
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How to include lifecycle configuration in Sagemaker studio's user notebook

I want to use lifecycle configuration in Sagemaker studio so that on start of user's notebook it runs the given lifecycle configuration. My lifecycle configuration will have shell script which will ...
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1answer
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How to aggregate features to a group level as a feature in machine learning model?

I am building a model to predict some behavior at a household level. I could roll up income or number of cars etc so that I can take everyone into consideration. But how can I roll up something like ...
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1answer
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with ML/DL model Is possible predict numbers of items required?

I have a dataset is regarding ambulance call data. Data sample: ...
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1answer
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Which data science framework should I start learning? [closed]

I have learned Python but am confused about which data science framework should I start off with? Matplotlib or Pandas or Numpy? Also, can you recommend which tutorials I should look for each one of ...
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1answer
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Can absolute or relative contributions from X be calculated for a multiplicative model? $\log{ y}$ ~ $\log {x_1} + \log{x_2}$

(How) can absolute or relative contributions be calculated for a multiplicative (log-log) model? Relative contributions from a linear (additive) model E.g., there are 3 contributors to $y$ (given by ...
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What models should I try with a time series database? [closed]

I've acquired and cleaned a dataset that shows statistics from every county in New York State during 2010-2019 focusing on the NYS School Aid correlating it to other growth and criminal statistics. ...
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1answer
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Semantic analysis score as input to LSTM model for improving stock price prediction accuracy [closed]

I have created a univariate LSTM model that is predicting value of Open Price based on last 5 years opening price of a particular stock. I'm getting a decent accuracy. Now, I want to do sentiment ...
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Robust Gaussian Fit

I have tried to find some literature on robust gaussian fits, all I could find was good old EM gaussian mixtures. The question is : given a mixture of gaussians, find the dominant one around a given ...
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2answers
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is it possible to decide model without any data?

Today I just faced a very unique demand from my superior. He asked me whether I can make a model first before we gather the data for training because we don't have any data yet. I was utterly ...
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1answer
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Cross-entropy via softmax: Mathematical derivation [closed]

I am trying to understand the derivation of cross entropy loss in the context of softmax. However, some steps are still not clear to me. Hence, I would appreciate if someone could please explain. y = ...
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1answer
29 views

What is “Missing” in output of plot_tree API of XGBoost

What this "Missing" term means here at each node after split in Image? and also what is at leaf, is this means prediction value? I converted Output variable to 1 and 0. I tried searching on ...
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best python library to extract the location from the text [closed]

Which is the best python library to extract the location from the text. Spacy and NLTK not recognizing the mountain names, river bodies properly. Could you please give me your suggestions? Thank you!
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1answer
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How to calculate an average cliff date?

Please let me know if this question belongs elsewhere. In my simple data set focused on sales pursuit opportunities, I have the following columns available. Pursuit Name Status(Open, Won, Lost) Date ...
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why do we need re-scaling ? Is it necessary for all types of data including interval and frequencies

Re-scaling seems to have become a fashionable technique. The methods have propped up to deal with several types of data. Moreover,it is applied without much of context. Should we use it for only ...
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1answer
154 views

Two steps optimization of a credit card limit

I have a problem similar to what is on the title but not the same, the problem on the title allows me to explain the dynamics of my need. I have to determine how much is the optimal value for a ...
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1answer
33 views

which Model to apply on panel data where unique id has 6-8 records and total records are 2,000,000?

I am new to such panel data where I have multiple observation for same ID in different Quarter and I am not sure what kind of machine learning algorithm I can apply. I have data from Q1-18 till Q4-...
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2answers
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How to identify patterns in dataset [closed]

I have a dataset that pertains to calls received to a hospital emergency helpline. My task is to identify patterns in the data. How do I approach examining the dataset to identify patterns? Extract ...
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2answers
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How do you use KS-test in a data science report?

I'm writing a data science report, I want to find an exist distribution to fit the sample. I got a good looking result , but when I use KS-test to test the model, I got a low p-value,1.2e-4, ...
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1answer
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Which data science model is best for explainability for prediction problems?

Imagine you have to create a model to explain to stakeholders e.g. to predict price, weight, sales etc.. Which regression models offer the best in terms of explainability and interprability? ... Which ...
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1answer
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Forecasting using Boosting methods on Non-stationary Time Series data

Theoretical Noob question - Can we use boosting methods to effectively forecast the future after being trained on a non-stationary time series? Or do you train/fit on the residual of the training set ...
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flexibility vs complexity vs number of predictors in machine learning

I'm new to machine learning so am quite confused with the above concepts. It seems to me both flexibility and complexity measures how well the model fit the data (in terms of the curvy-ness), so what'...
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Handling missing data - secondary driver characteristics in insurance data

I have an insurance dataset which includes an indicator that indicates whether the policy insures a secondary driver, and the secondary driver's age/sex. Problem is most policies do not have secondary ...
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I'm trying to quantify phasing… (unabashedly sports related)

I'm working to visualize NBA minutes wherein one player may have their playing minutes reduced, another player's minutes are increased. I've got the data laid out in a matrix of actual minutes per ...
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Data calculation/normalisation /data summarisation

Clustering is done based on houses data and say suppose cluster 1 contains 5 houses. Appliance 1 is used in 2 houses out of 5 and appliance 2 is used in 4 out of 5 houses.Each appliance produces an ...
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What are the business metrics I should track to evaluate a recommender model deployed on an e-commerce website? [closed]

Can you suggest some google analytics metrics such as (click or impressions etc) to evaluate a recommender model deployed on an e-commerce website.
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2answers
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Machine Learning for medical researchers [closed]

My friend is a medical researcher and he want to use machine learning for prediction. Is there any one who is not a computer science person and he learnt programming and machine learning in a very ...
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1answer
191 views

What is the difference between trax vs tensorflow?

What is the main difference between trax vs tensorflow? both of them deep learning library and implemented by google team. https://github.com/google/trax https://github.com/tensorflow/tensorflow
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How does stacking help Bias and Variance?

How does stacking help in terms of bias and variance? I have a hunch that stacking can help reduce bias but i am not sure, could someone refer to a paper?
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1answer
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What is the difference between cache() vs prefetch() in tensorflow?

I have gone through the TensorFlow documentation. What is the difference between cache() vs prefetch() in TensorFlow? When ...
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Confusion Matrix after XGBoost is showing positive as negative class

Please can you help me with confusion matrix. I've implemented the XGBoostClassifier. After fitting the model when I looked to the confusion matrix to view the performance on Test data. The confusion ...
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1answer
91 views

How to convert input numpy data to tensorflow tf.data to train model in tensorfow?

I am working on an image classification problem using TensorFlow. I have converted my input image dataset and label into NumPy data but it takes more time and more ram to load all the data into memory ...
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Forecasting Weekly Average Usage

In python/pandas what would you suggest as a couple of good basic methodologies to use to forecast weekly average usage of user activity on a given platform?
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1answer
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train test data split up in datasets

In a dataset consisting of 1,000 samples, it has been shown that a 70-30 split (i.e. 70% of the samples used for training, 30% for validation) will provide a good estimation of the test accuracy of ...
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How to correctly lemmatize the text column in R?

I'm working on a project in Natural Language Processing. I have a data frame that has a text column. I have to lemmatize that text column. I'm using lemmatize_strings() function in R. However, there's ...
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1answer
20 views

Microsoft custom vision vs Tensorflow model?

I am planning to implement my own image classifier model using TensorFlow instead of a custom vision platform. what is the biggest difference between custom vision(https://www.customvision.ai/) vs ...
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1answer
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what is difference between Logistic regression and SGDClassifier with log loss OR SVM and SGDClassifer with hinge loss?

Can we just use SGDClassifier with log loss instead of Logistic regression, would they have similar results ?
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Calculating the lower and upper bounds forVC-dimension of a decision tree

I have a problem finding the lower and upper bounds of the decision tree. Suppose there is a decision tree with a hypothesis space of depth 2 and an input space with 10 variables (the variables take ...

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