Questions tagged [prediction]

prediction is the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. The goal is to go beyond knowing what has happened to providing a best assessment of what will happen in the future.

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1answer
363 views

Why is predict_generator is returning an empty array?

I am trying to print the predicted labels of my test data but the predict_generator() function is returning an empty array. My Model: ...
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1answer
110 views

How to use spectral clustering to predict?

In an academic paper, they talk about using a nearest neighbour algorithm to predict the cluster of a new point. And how the number of nearest neighbours is set to 10 in their example. What do they ...
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1answer
175 views

YOLO Dense Prediction

I have two questions about dense prediction in YOLOv4 paper What does it mean by the (hard negative, online hard) example mining method is not applicable to one-stage object detector, because this ...
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2answers
253 views

why we sample when predicting with Recurent Neural Network

I trained a Recurrent Neural Network to predict the next word in a sentence. I trained and now I want to predict, but there is something I am not getting well. I saw it in many tutorials even in the ...
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1answer
2k views

How to make predictions of multiple input samples at once in tf 2 with keras

I am quite confused on the output of model.predict when after training I validate my model on around 6000 samples I use the following pseudo code: ...
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1answer
62 views

I am getting very minimal mse values and not sure if it is correct?

Below is the linear regression model I fitted and not sure if I am doing the right way as I am getting neat to 99% accuracy Fitting Simple Linear Regression to the Training set ...
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0answers
24 views

Derivative of multi-output Gaussian Process

I am working on a project where I estimate transition and measurements models for a kalman filter using Gaussian Processes. In order to linearize the models I require the Jacobian of the estimated ...
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0answers
96 views

Keras Bidirectional LSTM: low training and validation loss but very bad predictions

I'm training a Bidirectional LSTM using Keras. My task is to predict the words order in a sentence, so, given a sentence, ...
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0answers
288 views

PyTorch time series prediction beyond test data

I am currently playing around with pytorch models for time series prediction. I have managed to successfully run a model to predict test data. I was wondering how can I use it to predict beyond test ...
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2answers
985 views

Why do decision trees have low accuracy?

It seems to be generally acknowledged that decision trees have low prediction accuracy. Is there a concise explanation for why they have low accuracy? I've read this so much, I've accepted it to be ...
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1answer
83 views

How to incorporate the uncertainty of the model coefficients in the prediction interval of a multiple linear regression

I'm dealing with modeling small experimental data sets. As most experimental work does not generate thousands of samples, but rather a handful, I need to be inventive about how to deal with this small ...
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0answers
40 views

Difference between shap values and feature contributions

I always found both concepts a bit confusing since they are quite similar. Would someone provide clear example where to apply each? Shap values ref: https://towardsdatascience.com/explain-your-model-...
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0answers
35 views

How to calculate the prediction interval?

I am recently engaged in a project of predicting the future blood glucose values of the patient. I was able to get a lower RMSE and MAE by using Gradient Boosting Algorithm. But although the error is ...
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1answer
113 views

How to compute the prediction interval for unseen data?

I want to calculate the prediction interval of individual predictions without knowing what it's target value is gonna be. For example, I am doing a blood glucose prediction of individual patients and ...
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2answers
79 views

Binary classification problem with imbalanced dataset, how to compare to random classifier

We have a very imbalanced dataset (2% of class 1). To the best of our knowledge, there is no baseline in the literature to the problem we want to solve - so we thought of comparing our performance to ...
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1answer
806 views

Predicting the missing word using fasttext pretrained word embedding models (CBOW vs skipgram)

I am trying to implement a simple word prediction algorithm for filling a gap in a sentence by choosing from several options: Driving a ---- is not fun in London streets. Apple Car Book King With ...
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1answer
25 views

Can OLS regression be used to predict from a complete sequence of data?

Reading online and following this example from scipy I understand OLS can be used to find data between gaps in a sequence (interpolate?) but I already have a complete sequence and want to predict the ...
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1answer
17 views

prediction() returning mistakenly false positives [closed]

I do not know how to interpret the result of: prediction(c(1,1,0,0), c(1,1,0,0)) prediction() functino comes from prediction {ROCR} it has this site: ...
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1answer
35 views

Dissecting performance issues with Random Forest

My task is to identify potential situation for trading and determine whether a candidate is going to succeed or not. I have a system in place to identify candidates, but there is a high rate of false ...
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1answer
45 views

NN Model accuracy and loss is not changing with the epochs!

I am building a tensorflow model for Heart Disease Prediction data-set. It has a binary outcome (0, 1). Though I am struck with such a low accuracy which is not changing with epochs. ...
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0answers
34 views

Using Neural Networks on images to predict successful vs unsuccessful trades

The context for the problem is day trading: identifying the moment when one can buy units of a stock and then wait for them to grow in value before selling them at the new price. Currently I have a ...
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2answers
37 views

Which algorithm to use to identify clusters with a similar value?

Here, an example of my problem: 10000 observations of people with several features [age, gender, region, number of sons, ...] and a value to predict "income". There is not a general relationship ...
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1answer
61 views

Is there any way to calculate the true,false positives and negatives for a regression problem

I am trying to predict the glucose values of the patients for example values like 45,256,115 etc. based on some features. Currently I am calculating the accuracy in means of RMSE,MSE,R². Is there any ...
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2answers
37 views

Classification with feature not available at time of model creation

I have problem statement to predict the probability of solving a task depending on multiple features for e.g. when the task was created, the time needed to work on a task, etc Please find a dummy ...
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2answers
289 views

How to cluster categorical and numerical data in the same dataset?

I have a dataset in which it contains both numerical and categorical data. This can be done using supervised learning algorithms, but I am eager to see how this data can be clustered using some ...
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1answer
69 views

Class asks me to give self for Naive Bayes Model python

I try to use the following code but when I try to use fit function with my X_train and y_train, I get the following error: <...
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1answer
35 views

what metrics to evaluate rank order results?

I have searched on stackexchange and found a couple of topics like this and this but they are not quite relevant to my problem (or at least I don't know how to make them relevant to my problem). ...
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1answer
49 views

Unable to make accurate predictions?

I have a dataset of diabetes patients and I am trying to predict the next blood glucose level. I have attached an image below and I have about 1600 records in that csv file containing data of 10 ...
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1answer
24 views

Machine Learning - How to predict set of fixed fields based on past features

I have quite a large dataset (> 100k rows), which contains information for logistical shipments. (export shipments) The dataset looks like this: ...
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1answer
474 views

ML methods for prediction, using categorical variables and time

Most of the time series analysis tutorials/textbooks I found time series data, usually deal with continuous numerical variables. I am currently trying to solve a problem that deals with multivariate ...
2
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1answer
142 views

How to deal with different length entities in a Keras DataGenerator?

I'm solivng a prediction problem where I need to predict the demand of multiple articles based on their performance during the last 7 days. To get the most out of the data I am trying to implement a ...
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1answer
21 views

Dealing with issues in "test" predictons for single "items" (null values, standardization in place, etc)

I know this is kind of a broad question but I have tried to scour both this forum and the internet in general to no avail for this particular situation. So imagine I have a model trained for which, ...
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1answer
107 views

Prediction for Current month based on last month's Labels

I have monthly data of loan installment repayment. The data contains basic features like salary, age, gender, credit score, etc. Along with the above features, I have the data for the last 6 ...
5
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1answer
169 views

which algorithms can be used to extrapolate non-linear data?

I have a dataset, where target value changes in time in following way: I need to predict target value for upcoming month, however I struggle to find a method to extrapolate the function that defines ...
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1answer
27 views

Can sampling like SMOTE/UP/DOWN applied on Validation set?

I am trying to predict classification problem. For that I have used Ranger, Xgboost and naive bayes. My Response class is imbalance . 92:8 ratio. My positive Response is only 8% of whole data. ...
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1answer
969 views

Calculate confidence score of a neural network prediction

I am using a deep neural network model to make predictions. My problem is a classification(binary) problem. I wish to calculate the confidence score of each prediction. As of now, I use ...
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1answer
69 views

Why does MAE differ after prediction (Neural Network)?

I'm having trouble understanding what's happening in the following code. I already have defined x_train, y_train, x_val, y_val and x_test which define my training, validation and test sets. I'm using ...
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1answer
132 views

Using Majority Class to Predict Minority Class

Suppose I want to train a binary model in order to predict the probability of who will buy a personal loan and in the dataset only 5 percent of the examples are people who marked as bought a personal ...
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1answer
68 views

Time Series Classification for loan data

I have multiple columns for loan installment repayment. As there is a field for month of repayment, I want to predict if the customer is going to pay next month's installment or not. As I have ...
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1answer
78 views

How to use random forest model to new data?

I am new to this Data Science field. I have a question to apply Random forest to new data. I have this table. ...
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2answers
73 views

prediction using LSTM

i have training data from 2015-2017 and testing data of 2018. i have multiple variables my data is multivariate time series data.i want to predict 2019 data by using test data of 2018.is it possible? ...
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1answer
98 views

Terminology - regression with one output and multiple output variables

I am trying to predict the response when the input is represented by Fourier transform. These form the features and are typically represented as a vector, $x_1,x_2,...,x_d$ where $d$ is the length of ...
3
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1answer
3k views

Making predictions / Loading model in TensorFlow 2.0

I use TensorFlow/Keras on a daily basis to make predictions for a project. Everything works fine but I was getting regular warnings about the transition to TensorFlow 2.0 and I thought this week I ...
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0answers
21 views

Loss is decreasing but the predictions are not getting well

I am trying to implement a Dependency Parsing model using the transformer model in here with a few changes. On the training, my loss has decreasing trend; but the predictions at the end of 20 epochs ...
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1answer
180 views

Making predictions with missing numeric data

I don't know much about how to deal with missing data. When the data is categorical it doesn't seem too bad, if I one-hot encode it without dropping any of the actual categories, the missing data is ...
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1answer
36 views

How to forecast labels forward 3 years

I have many variables that I am using to predict median gross rent. I want to predict forward 3 years this is what my labels look like: How do I either preprocess the data in order to get a 3-year ...
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0answers
146 views

Prediction issue with xgboost custom loss

I have an issue with xgboost custom objectives: I do not manage to get consistent forecasts. In other words, the scale of my forecasts is not in line with the values I would like to predict. I tried ...
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0answers
29 views

Predict with some probability the day of the month paycheck received through daily transactions

I am using R to do machine learning. I have daily shopping expenditure data of individuals over a couple of months and my goal is to be able to identify through their shopping pattern the day of the ...
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1answer
44 views

Which Machine Learning methods would be good for a beginner-level Data Science project for described dataset? [closed]

I want to do my first beginner-level project regarding Data Science. I picked my data set which is described below. I want to make a Python script which will make some predictions on our data set ...
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1answer
254 views

Why the first prediction of neural network in PyTorch is slower than following predictions?

So I have ResNet50 trained to classify images. For each prediction I track the time needed for it (input and model are moved to GPU): ...

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