Questions tagged [prediction]

The tag has no usage guidance.

Filter by
Sorted by
Tagged with
0
votes
0answers
18 views

How to estimate the OCR accuracy

I am building a system which uses ocr to extract text but i have no way to flag that information on how correct it can be and if the information needs to be discarded by just looking at the image and ...
-1
votes
0answers
12 views

how to predict next randomly picked element of a list

The Problem Let's say that we have a machine that spits out a number (between 1 to 15) alongside a color (either green or blue) every 10 seconds. OK so every 10 seconds we get a number (between 0 to ...
2
votes
1answer
137 views

Combining scaling, dimensionality reduction, prediction using sklearn pipeline

I would like to use a sklearn pipeline doing this : ( - ) scale the data ( StandardScaler ) ( - ) reduce dimensionality ( PCA ) ( - ) make a prediction with GradientBoostingRegressor() and ...
1
vote
0answers
10 views

When should I reverse normalizations to evaluate loss?

If I am training a neural network and have normalized the data before-hand, should I reverse the normalization to calculate the loss? This tutorial provides an example of this method. What if I'm ...
0
votes
1answer
72 views

Very low probability in naive Bayes classifier 1

I have some training data (TRAIN) and some test data (TEST). Each row of each table contains an observed class (X) and some columns of binary (Y). I'm using a Python script that is intended to predict ...
-1
votes
0answers
9 views

Number prediction [closed]

I would like to know if I could predict the next number from a large available sequence of numbers using orange. If so please help me with the detailed steps as I am new to this field.
1
vote
1answer
31 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: ...
2
votes
1answer
2k views

XGBOOST : model.predict_proba() and model.predict() conflicting behaviour

I have two classes : 1 and 2 The output of model.predict_proba() -> [0.333,0.6667] The output of model.predict() -> 1 This is happening for around 200 test values out of the test data of 10 lac. ...
0
votes
1answer
38 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 ...
0
votes
1answer
118 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....
0
votes
0answers
10 views

Predicting the future event given the past sequence and backward

I have a problem of event sequence modelling and I want to model it with Artificial Intelligence (ML/DL) but I am not sure which algorithm to start with, I want to start simple instead of applying ...
0
votes
2answers
2k views

What algorithms are good to predict next numbers?

Let's consider we have several hundreds of numbers like ( 1, 2, 5, 8, 7, 15, 19, 8, 4, 6, ...) those are closed numbers of a stock on consecutive days for example. I like to know what algorithms are ...
2
votes
1answer
29 views

Predicting probability for each tag given already chosen tags

I have a set of tags (~10'000, will be extended over time) presented to a user. After he has selected 3 or more tags, I want to predict for each remaining tag what the chances are that the user will ...
0
votes
0answers
11 views

Measuring chance (“risk”) of being in some class

I don't know if this question fits better here or in statistics, but I think here is more appropriate. I have a dataset with several companies and its features and also I have the information if they ...
-1
votes
0answers
15 views

it make sense to re-train a ml model every step?

my boss asks me to build a model (LSTM) like this: I have a series called Data/ len(Data)=5000. I split it into Data_train=Data[:-300] and Data_test=Data[-300:]. ...
2
votes
1answer
816 views

Estimating Predictive Uncertainty for unlabeled data

I am trying to estimate the predictive uncertainty for a deep neural network. While I do have a labeled training set, I´m trying to measure uncertainty for some unlabeled production data. This paper ...
0
votes
1answer
37 views

Two-class model with predicted scores needed - classification or regression approach

In my problem, step one is to build a model to classify cases as one of True or False (1 or 0 could also be used obviously). Once the optimum model is found, step two is to retrieve probabilities for ...
0
votes
1answer
824 views

How to Predict/Forecast street's Traffic based on previous values?

I have a dataset which has the following 5 columns: date, hour, day_of_week, street_id, counts My dataset has information about the number of cars that each ...
3
votes
2answers
79 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 ...
0
votes
0answers
19 views

Which type of model should I use to predict when a time-series value will revert towards the mean?

I have a time series that consists of many rows, each with a timestamp, and a value between -1 and 1 representing the normalized price distance between 2 financial assets. Each entry is roughly evenly ...
0
votes
1answer
20 views

How to measure model success in production

I have a model running on a productive system. The model predicts if some lead will become a sale. How would you develop a check, which checks the success and the accuracy of the model? There is a ...
0
votes
1answer
13 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: ...
2
votes
2answers
56 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 ...
1
vote
1answer
14 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 ...
0
votes
0answers
31 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 ...
0
votes
2answers
41 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? ...
2
votes
2answers
405 views

what is the interest of TimeDistributed after an LSTM layer?

I've already seen several similair questions but I did not understand anything, what is the interest of TimeDistributed? why we need to insert a TimeDistributed layer after LSTM to establish the time ...
0
votes
0answers
20 views

Simple revenue predictor

I'm trying to create a program which should estimate the total revenue for current year by analyzing the payment data from this and previous years. Generally, it's about a subscription-based SaaS ...
0
votes
1answer
22 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 ...
3
votes
1answer
991 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 ...
0
votes
0answers
17 views

Orientation on a Genetic Algorithm approach for the Financial Forecasting

So there is these article: Brown, M. S., Pelosi, M. & Dirska, H. (2013). Dynamic-radius Species-conserving Genetic Algorithm for the Financial Forecasting of Dow Jones Index Stocks. Machine ...
1
vote
2answers
71 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 ...
0
votes
0answers
14 views

Weighted RMSE in RNN for Multivariate Time Series: Deal with different Starting Dates and Mini-Batch

I am doing Multivariate Time Series prediction with Deep Learning. My metric is a Weighted RMSE (where each serie has its own weight), and I am trying to implement the WRMSE as my loss function for my ...
4
votes
1answer
155 views

Why does CV yield lower score?

My training accuracy was better than my test accuracy, hence I thought my model was over-fitted and tried Cross-validation. The model further degraded. Is that my input data need to be sanitised ...
1
vote
2answers
3k views

ValueError: Expected 2D array, got scalar array instead using predict method

I am trying to get a predicted value instead of whole features for a particular level using predict method. ...
0
votes
0answers
8 views

Incorporating a neural network into prediction algorithm

I created a linear and quadratic regression algorithm that uses a brute-force approach to map out the best equation for a data set. However, my model is quite slow (it takes 4-5 seconds) and is VERY ...
0
votes
1answer
121 views

what is the best approach to my prediction problem

I'm trying to predict occupancy for every floor in a building (with the primary focus on only one "proof of concept" floor for now). I have a lot of time-series data, that tracks user's logons and ...
0
votes
1answer
30 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): ...
1
vote
0answers
13 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 ...
0
votes
0answers
17 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, ...
0
votes
1answer
199 views

Machine Learning based Multivariate Time Series Prediction - How to create supervised data format

Q1: I have a multivariate time series dataset. For each timestep, there are 11 features and 1 output. I am going to use supervised ML to predect the output. I understand that in univariate cases, if ...
1
vote
2answers
453 views

Train an LSTM neural network with time series containing seasonal and trend

I am working on a project for predicting the number of DNS queries from the site: DNS queries statistics. The data I use is minutely data, which means the number of DNS queries of every minute. If ...
0
votes
1answer
778 views

Predictions with arbitrairy sequence length for stateful RNN (LSTM/GRU) in Keras

I have time series data of the following properties: input shape: (num_timesteps, num_features) output shape: (num_timesteps, num_outputs) I reshape it to batch ...
1
vote
1answer
143 views

Predicting Customer Activity Absence

Could you please assist me with to following question? I have a customer activity dataframe that looks like this: It contains at least 500.000 customers and a "timeseries" of 42 months. The ones and ...
1
vote
1answer
50 views

predicition for a specific month

I am attempting to build a predictive model based on the past historical data. I have details of specific machine failure based on the past year data. I have data from some months of 2016 and from ...
0
votes
1answer
23 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 ...
1
vote
0answers
38 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 ...
1
vote
2answers
590 views

Is it possible to use the saved xgboost model (with one-hot encoding features) on unseen data (without one-hot encoding) for prediction?

I think the question is self-explanatory. But let's say you have a data with a few features with categorical data, and when building a model for example XGBoost you one-hot encode categorical features....
0
votes
0answers
18 views

Why does the Neuralnet package predict constant values when a second hidden layer is added?

I'm trying to use a multi-layered neural network to predict concrete strength, using R's neuralnet package. Everything works great with a single layer, but when a second layer is added, the ...

1
2 3 4 5
7