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Questions tagged [prediction]

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8 views

AQI prediction using machine learning [closed]

Air quality index can be calculated using formula? Why are we using machine learning algorithms to predict AQI?
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1answer
17 views

Rule based prediction for known data

Lets say we have trained our model on 900 records (training data) . During prediction on test data of 100 records, assume model produces 95% accuracy. The question here is, can a mechanism be built, ...
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1answer
18 views

Random Forest. In a prediction less input is expected than features used

ValueError: Number of features of the model must match the input. Model n_features is 2 and input n_features is 7. I have the following error: I have not used any type of encoding(like one-hot etc.) I ...
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0answers
11 views

Error while using pre-trained model

I'm working on NLP task using RoBERTa model. As training last very long I saved my model, but now for some reason, part of my code doesn't work with this pre-trained model (getting an error), and ...
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0answers
24 views

Is there a dataset that can predict duration to complete a task using task description? [closed]

I am working on a problem where the task is to predict how long will it take to complete a given task using just the description as a feature set. The description is something like "pick up X and ...
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1answer
27 views

How do you effectively predict the top 20% most likely customers to churn from a dataset?

I am looking to work out that if I have a dataset with 100,000 existing customers who didn't churn and 20,000 previous customers that churned in the past and the business objective is to target the 20%...
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0answers
30 views

Time series forecasting for vibration prediction on Industrial machine production?

I'm working on a machine learning project related to an industrial machine. The goal of the project is to build a model that would be able to predict the vibration of the machine while it's in ...
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0answers
9 views

Minimising inputs for decision tree predictions

It is common for decision trees with asymmetrical shapes to have leave nodes that come early. For example, the model can already generate a prediction if the answer to the first question is FALSE, ...
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0answers
9 views

Forecasting mon missing time timeseries data

I have time series data for minutes interval. But due to some noise i have to remove some rows from data. Now, I have data with some missing time stamp. What should i do for forecasting in this case?
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1answer
20 views

Keras: Provide One-Hot-Encoded input values to neural network

I have a dataframe which has two columns of interest: A and B with string values. I am trying to build a prediction model which takes in a set of values in A as input and predicts the corresponding B ...
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0answers
10 views

Multiple Input (Binary) and Single Ouput: How to calculate correlations?

I have a dataset with multiple criteria which are either "passed" (green) or "not passed" (red) and an output (passed or not passed) -> see table. Also the criteria have a ...
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0answers
44 views

Divergence of Specificity and Sensitivity

I am working on a ML classification project in healthcare. The data is imbalanced, and I decided to start modeling with tree-based algorithms such as (Balanced)RandomForest and XGBoost. While checking ...
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1answer
22 views

How to get periodicity from timeseries data?

I would like to create a recommendation system for a smart home application. I gather the data in a time-series database. The app monitors the on/off state of a smart lamp and can create daily ...
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1answer
31 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 ...
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0answers
13 views

Can I use depth prediction map to infer horizontal distances?

I have a hardware + software setup that uses a sensor to give good estimates of depth, onto a pixel map - think Kinect or similar. Example below for context: Now assume I can access individual pixel ...
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0answers
18 views

Predicting in decision rules

Sequential covering is a type of decision rule procedure that repeatedly learns a single rule to create a decision list (or set) that covers the entire dataset rule by rule. Given a training dataset, ...
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2answers
33 views

Warning when plotting confusion matrix with all sample of one class

I have two arrays: the first one with all the correct labels (they are all set to zero since each sample belong to the same class) and another one with all the labels predicted by my neural network. ...
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0answers
10 views

How can I intuitively calculate the accuracy of my financial prediction model?

I've built a SARIMAX model based on my personal spendings record as a college thesis and have reached a point where I'm pretty content with how it turned out and am getting ready to start writing the ...
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0answers
14 views

Demand Prediction (Retail Sales) Datasets for Benchmarking

I've been looking for 2 days and can't seem to find what would normally appear as trivial: a Time series (preferabl daily or intra-day resolution) Demand or Sale Labelling Retail Dataset Preferably ...
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0answers
8 views

Machine learning model to predict performance degradation over period of time

I am new in ML space and working on the task to build a model that would predict performance degradation of integration bus in real time or "almost real" time. The idea is fairly ...
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0answers
20 views

Difficulty understanding the difference between Poisson, Quasi-Poisson, and Negative Binomial models

I will try to keep this short. As an assignment for my GLM course, we were given a dataset on the # of homicide victims a person knows, as well as the race of the person. The main idea is to answer ...
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0answers
15 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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0answers
19 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
71 views

How to read the predicted label of a Neural Netowork with Cross Entropy Loss? Pytorch

I am using a neural network to predict the quality of the Red Wine dataset, available on UCI machine Learning, using Pytorch, and Cross Entropy Loss as loss function. This is my code: ...
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0answers
8 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
52 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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1answer
293 views

Found input variables with inconsistent numbers of samples: [30, 24]

I'm using neural network machine learning and would like to see the result of my confusion matrix for my model. However, there is an error that I've got and don't know how to solve it. ...
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0answers
13 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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0answers
19 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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0answers
17 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
25 views

How to use prediction model after onehot encoding?

I have created a prediction model for this dataset ...
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2answers
329 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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0answers
13 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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1answer
63 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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0answers
39 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 ...
0
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1answer
107 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
89 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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2answers
77 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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2answers
28 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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1answer
23 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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0answers
52 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
26 views

Does my prediction improve when I use more, but worse classifiers?

I have a logical problem when programming my tumor identification algorithm. In my data sample, I have tested multiple antibodies on tumors - to identify whether those tumors are good or bad. This is ...
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0answers
31 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
22 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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0answers
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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0answers
38 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
91 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 ...
-1
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1answer
44 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 ...
0
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1answer
32 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 ...
0
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1answer
126 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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