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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16 views

Angle prediction

I am working on an assignment for neural networks and I need to predict an angle. firstly the last layer of the neural network directly predicts the angle, secondly, the last layer gives as an output ...
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1answer
18k views

What do "compile", "fit", and "predict" do in Keras sequential models?

I am a little confused between these two parts of Keras sequential models functions. May someone explains what is exactly the job of each one? I mean ...
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20 views

History that lead to the word "predict" being used for the application of a model on data

Background The framework scikit-learn uses "predict" for the application of model on (new) input data and I have seen many people use that term. In the scientific papers that I have read (...
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2answers
275 views

Scikit-learn pipeline with scaling, dimensionality reduction, average prediction of multiple regression models, and grid search cross validation

I would like to use a sklearn pipeline doing this : ( - ) scale the data ( StandardScaler ) ( - ) reduce dimensionality ( PCA ) ( - ) make a prediction with GradientBoostingRegressor() and ...
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91 views

Predicting the likelihood that a prediction from a linear regression model is accurate

So to set up the problem: I have a data set that had labeled data like colour, brand and quality as independent variables and the dependent is RRP (price). I have made a linear regression model using ...
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9 views

Should I give regularly-spaced or irregular-timestamped data to a price predicting neural network?

I am building an application to predict the price of an item. Data is collected at regular 5-minute intervals while the application is running. Unfortunately, there is downtime, so there is not a full ...
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3answers
53 views

How to decrease $R^2$ value and change it to positive value [closed]

I'm working on a data, and use regression , as you see bellow: from sklearn.svm import SVR regressor = SVR(kernel = 'linear') regressor.fit(trainX,trainY) above ...
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78 views

Make image label prediction from Chainer CNN model

I have train dataset of 8000 images and labels. Validation set consists of 1957 images and labels. The test set contains 2487 images. Each image contains White Blood Cell images. WBC is divided innto ...
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2answers
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New to Data Science - What to use when looking for a pattern/relationship between items and an outcome

I am new to data science and I am hoping I can start applying it to my job. I have watched some videos on places like Udemy for Machine Learning and Python etc. Anyway, I have a task but I am not ...
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1answer
26 views

Predicting complete time series for given parameter sets

I am searching for an approach that is able to predict a complete time series for a given parameter set. Imagine a robotic arm which has a starting position and a target position. There is a sensor ...
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16 views

Unseen samples(Rare category) during prediction?

Say if I train on these features(combination of categorical and numerical data), we could see that in feature x2, sample 4 has a rare entry 'b'. if during my train test split, I end up not getting ...
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5answers
56k views

Time series prediction using ARIMA vs LSTM

The problem that I am dealing with is predicting time series values. I am looking at one time series at a time and based on for example 15% of the input data, I would like to predict its future values....
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22 views

How to do prediction on survival data, using Random Forest

I should make prediction on survival data, using the random Forest method. My question is: should I follow the same approach as in logistic regression? taking into account only the status variable or ...
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1answer
152 views

LSTM model prediction scaling with loaded model

I am deploying a LSTM pytorch model for production and I have issue with scaling the LSTM output correctly. While the model was tested the output was scaled with label data: ...
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33 views

Predicting next rows in tabular dataset

I have a tabular dataset of financial transactions with a target binary variable 'isFraud' which indicates if the transaction is fraud or not. I want to build a model that given some past trasactions, ...
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0answers
19 views

Feature Engineering and prediction with R and python

I have a sequential dataset, and have 2000 rows for 300 ID. I have 20 variables (i.e in my real dataset) ...
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1answer
82 views

How to use prediction model after onehot encoding?

I have created a prediction model for this dataset ...
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2answers
561 views

Speed up Keras Model Prediction Load Times

I am trying to create a prediction API using keras which loads the model predicts and closes the model. But initializing time in python is about 3-5 secs so each request takes around 5 secs to return ...
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14 views

Preparing and combining datasets for predictions

I am trying to create and train a model to predict the winner of a professional DOTA match. This model is only for "fun" and shouldn't be used for ...
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2answers
3k views

Encode multi-class response variable

In a classification problem when the response variable has multi-class, e.g., "sunny","rainy","cloudy", how should we encode it? I know that for predictors like this, usually we do One Hot Encoding, ...
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1answer
25 views

Predicting invoice data of 12 month using only 1 month data

I have only 1 month of historical data of invoices can I predict next 12 month of data with good accuracy if it is possible then which model should I used for prediction? Thanks
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2answers
1k views

Running examples from scikit-learn tutorials

I am new to scikit-learn. I went through the examples given in the docs and I downloaded the script for recognizing images of hand-written digits. When I made the script to run on my laptop, I got the ...
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1answer
85 views

How to reconstruct a scikit-learn predictor for Gradient Boosting Regressor?

I would like to train my datasets in scikit-learn but export the final Gradient Boosting Regressor elsewhere so that I can make predictions directly on another ...
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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 ...
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0answers
55 views

How to predict out-of-sample observations with depmixS4 package in R?

I have a series of univariate data and I want to fit a Hidden Markov Model on it using the depmixS4 package on R. My final goal is to predict the next k observations (let's say k = 10) for the data ...
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1answer
1k views

How to properly predict date using Orange 3

First of all - I'm new to all of this. I'm trying to create a model to predict the release of ios 12 based on previous years. I've got an excel that has a format like this: ...
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1answer
137 views

Encoder-Decoder LSTM for Trajectory Prediction

I need to use encoder-decoder structure to predict 2D trajectories. As almost all available tutorials are related to NLP -with sparse vectors-, I couldn't be sure about how to adapt the solutions to a ...
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0answers
132 views

LSTM giving almost constant output

I have used an LSTM with 4 layers deep each layer having 10 LSTM units to predict the AAPL stock 500 steps away by looking 50 steps back and it was predicting well (only a lag was there). However when ...
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1answer
6k views

how to interpret predictions from model?

I'm working on a multi-classification problem - Recognizing flowers. I trained the mode and I achieved accuracy of 0.99. To predict, I did: ...
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2answers
29 views

Can we consider high correlation to be a good predictor?

The problem of predicting the daily number of COVID-19 cases is indeed challenging and many (external) factors should be taken into account to come up with a reasonable predictor. However, we have ...
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0answers
58 views

Is padding the right way to allow your model to make prediction with test sequences of shorter lengths?

Say I have a RNN-lstm encoder-decoder model trained on fixed timesteps (no padding when training, all sequences are treated as if having the same lengths). My testing criteria requires me to provide ...
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1answer
3k views

clarification on train, test and val and how to use/implement it

So far I think I understood the differences between the training, test and validation set. Basically it is like in this image: Training set: The data where the model is trained on Validation set: ...
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35 views

Effect of batch during prediction

During prediction (not training), is it normal to get different loss for different batch size? Worst case happens when I use batch_size=1 for test dataset. The prediction performance get pretty bad. ...
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15 views

Confidence interval for class membership probabilities

I would like to calculate confidence intervals for predicted probabilities of a class membership obtained with randomForest. I know I could use predict.all in randomForest(), which gives me the ...
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43 views

*(CATEGORIES[int(prediction[0][0])])* giving me different result for single image prediction from saved model

From a saved model, I am trying to predict a single image. I followed this code - https://www.youtube.com/watch?v=A4K6D_gx2Iw I am getting different result for two different command- ...
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2answers
110 views

how do I predict the next's alarms ? (time series) [closed]

I'm trying to solve a time series forecasting problem, where the main goal is to read data with various alarm logs and make a prediction about what may happen in the future. Specifically, my data is a ...
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1answer
45 views

Algorithm for Multivariable timeseries prediction (COVID forecast)

I am trying to forecast tomorrow's COVID-19 cases in my country. I tried a simple Linear Regression implementation based on the "new_positives" field but it does not work very well. I had ...
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1answer
58 views

Predict real world data after modelling with scaled features [duplicate]

I trained and test a model with scaled features. Now, I want to predict a single real world sample. If I have one sample alone, I can't scale it to fit into the model like I did with the test data. I ...
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1answer
200 views

Is it possible to predict sentiment of unlabelled dataset using BERT?

I have a large unlabeled dataset and I want to predict sentiment for each document in this dataset. I want to know, is it possible that I can use BERT for sentiment analysis of unlabeled data? I have ...
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1answer
50 views

Sir Rod Stewart's and Celine Dion's voice after 15 years i.e. Year 2035 [closed]

https://www.google.com/search?sxsrf=ALeKk03hQn_rH1aaf7yO0q7CgN7CxPw2vw%3A1601345036018&ei=DJZyX9BW_o_j4Q-Fn77QCg&q=rod+stewart+age&oq=Rod&gs_lcp=...
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0answers
23 views

Why does my model fail to predict on the whole dataset?

So I have about 3000 images with 6 classes and this is what I did: 1 - split into training set and test set prior to anything with 20% test size 2 - performed data augmentation on the under ...
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1answer
68 views

How to approach the dataset with a continuous and discrete label?

Let's say you're predicting the amount of money to bet in a poker game. Based on the game situation, you might decide to fold. In that case, the amount of money to bet is zero. If you decide to call ...
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1answer
74 views

Predicting game scores using sklearn

I am using onehotencoding and RandomForestRegressor to predict scores of a set of soccer games. How can I use it into ...
5
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1answer
137 views

Understand the equations of quantile regression forest (Meinshausen)?

I am trying to implement a quantile regression forest (https://www.jmlr.org/papers/volume7/meinshausen06a/meinshausen06a.pdf). But, I have some difficulties to understand how the quantiles are ...
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1answer
173 views

Can I test my already trained model using the data it was trained on?

I have a model that predicts multiple choice answers to questions. I used an 80/20 train test split of my questions and tuned it. The questions actually form part of a game aka 10 questions in a game....
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1answer
87 views

How to use a multiple linear regression model built from normalized data

I built a linear multivariable regression model from normalized data (for the interval [0; 1]). Initially, the data was not normalized, I normalized the data by myself (independent and dependent ...
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1answer
216 views

Machine Learning: Predicting target based on a feature

I have a df looks as follow: -It is very likely that the same feature1Xfeature2Xfeature3 combination will appear multiple times....
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0answers
20 views

Stabilize Neural network prediction for class probability

I could not carry my question from stackoverflow I ve been trying to fit a neural network for binary setting using library(keras) and I am interested in class ...
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2answers
254 views

How to predict unknown unknowns in machine learning

I am dealing with a problem about classifying bird species through analysing MFCCs. I already built a dataset with 13 MFCCs for two kinds of birds. And I trained the data with Naive Bayes & KNN ...
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2answers
109 views

Is ARIMA appropriate for time series prediction involving a mix of explanatory and independent variables?

I have a table with the following columns: Date(Month,Year), Sold_Past_Month, Quantity_Available, Quantity_Shipping_In, Missed_Sales, Quantity_Needed Quantity_Needed is the dependent variable that ...

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