Questions tagged [predictive-modeling]

Statistical techniques used for predicting outcomes.

Filter by
Sorted by
Tagged with
0
votes
1answer
30 views

Comparing different classification results with different trainig and test data

I have different samples with different sizes. The instances of each sample have different features in comparison to the instances from the other samples. For each sample i train my model and tested ...
9
votes
2answers
2k views

Machine Learning Best Practices for Big Dataset

I am about to graduate from my Master and had learnt about machine learning as well as performed research projects with it. I wonder about the best practices in the industry when performing machine ...
4
votes
2answers
59 views

Which classification algorithms are negatively affected by class imbalances?

I've seen a few posts and papers floating around the web (mostly those related to over/undersampling, SMOTE, and cost-sensitive training) that, when discussing class imbalance, specify that certain ...
0
votes
2answers
198 views

Retrieve user features in real time from UserId for prediction

Let's say I'm building an app like Uber and I want to predict the user's most likely destination based on the user's past history, current latitude/longitude, and time/date. Here is the proposed ...
0
votes
1answer
21 views

How to measure Covid impact by analysing credit card transaction of customer

I Want to know how can I identify that is the customer is in financial distress due to the COVID situation using its credit card transactions. I have a daily transaction of customers till current ...
1
vote
1answer
21 views

best NN architecture for point prediction

I'm training to predict a single value y (continuos in [0,1]) based on a number of variables ...
0
votes
1answer
72 views

1: 10 rule in logistic regression - EPV

I have a dataset with 4712 records. Label Yes - 1558 records and Label No - 3554 records. I read online that ...
0
votes
1answer
22 views

How to adjust/smooth a certain number using constants or rules

Hi, I am handling a dataset with a customer purchase history. The field ord_cnt represents the purchase without coupon usage, and cpn_ord_cnt represents the purchase with coupon usage. There are two ...
2
votes
1answer
30 views

Prediction for not completely well classified data

I have a DataFrame of users, some of them are "bots" and they are identified with a bit equal to 1 in the "is_bot" column, if the bit is 0, the user is considered as "human". The problem is that some ...
0
votes
2answers
20 views

Custom loss function

Is it possible to apply a custom loss function in a regression model (or any other algorithm for predicting continuous variable) ? I'm working on a stock market prediction model and I need to maximize ...
1
vote
2answers
61 views

Which predictive model is appropriate?

I'm completely lost when trying to choose the type of predictive model for my problem. Is it autoregressive model, nonlinear time series, Markov Chain or other? Can someone please give me some advise? ...
0
votes
1answer
12 views

Identifying members who are likely to move to a lower cost alternative product

Overview: I am looking for some technical direction from the ML/data science community about how I could tackle my business problem. Context: In a nutshell, I have a group of customers who ...
0
votes
1answer
22 views

How to make prediction using tensorflow models?

As a newbie to tensorflow, I am using this tutorial from google for binary classification using a simple dense neural network. The slightly annoying thing about this (and a few other) tutorials is ...
0
votes
0answers
7 views

How to calculate final AUC for sequential combinations of binary classification models in Python

I am working on developing a binary classification model using GradientBoostingClassifier on a highly imbalanced dataset (100:1) that I plan to implement in 2 steps. build a model (M1) that will try ...
0
votes
0answers
12 views

Choosing a non-linear regression model and predicting

I'm new to data science and machine learning. I was working on a project and I happened to get this graph. I want to build a predictive model using this, for each of the boroughs. I do understand ...
0
votes
0answers
9 views

What should I use to model a non-monotonic relationship with values between 0 and 1?

I am trying to find a good model to fit to these curves: They are relationship between the probability of a dispute escalating into war, and the number of disputes in the past ten years between those ...
0
votes
0answers
7 views

can i compare output from predict_proba with my y_test value?

all, i am a bit confused at comparing my results from predict_proba (which returns an array) to it's dataframe e.g ...
0
votes
0answers
14 views

Public benchmark datasets posted with expected/record scores for sanity check?

When I use a new modelling tool or approach, I like to do a quick sanity check on a public dataset to make sure I'm getting good (but not "so good it looks fishy") scores. There are several clean, ...
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
27 views

Update the saved model after training

Will saving a trained model this way give me a model trained on every chunk of data or just the last chunk? ...
0
votes
0answers
13 views

Building the right prediction process with machine learning

I am working on a two-class classification model to predict if some lead becomes a sale. At this moment I have all leads try to predict these ones, which are sales. I become good metrics right now ...
0
votes
0answers
9 views

Predict users $ value based on selections

I want to predict the chance of a user becoming a customer, and subsequently predict their customer value based on inputs from a new user onboarding questionnaire. In the onboarding a new user can ...
0
votes
1answer
31 views

multiclassification dataset with many features giving very bad accurace predictions

I have been trying to fix this for 2 months now with no luck. I am doing some medical research for my study. I have a dataset that has patients diagnosis based on medical reports (Features.csv) and ...
1
vote
1answer
404 views

Connection between cross entropy and likelihood for multi-class soft label classification

The connection between cross entropy and log likelihood is widely expressed for the case when sample multi-class labels are one hot binary vectors (basically the same). Cross entropy is defined when ...
2
votes
1answer
122 views

Model prediction on meshgrid in python

Suppose I have data with two independent variable $X_1$, $X_2$ and one dependent variable say $y$, as follows: $X_1$: $x_{1,1}$, $x_{1,2}$ , $x_{1,3}$ $X_2$: $x_{2,1}$, $x_{2,2}$, $x_{2,3}$ $y$: $...
0
votes
0answers
16 views

Defining the Target Value

im new to this community and it always helped me with my concerns, i looked for an answer but didnt find a clear one yet im working on study for insurance default, the data i received is already ...
1
vote
3answers
32 views

Does shuffling data for time series forecasting help?

So I am trying time series forecasting using LSTM's. The aim is to predict $Y$ given $X$ using regression. I had already converted the input data into a sliding window format such that if my input ...
0
votes
0answers
19 views
0
votes
1answer
29 views

Logistic regression based prediction model using flask(python) to predict if Student will pass or fail. Error [duplicate]

I am trying to create a web application on Python using Flask that predicts if a student is likely to pass or fail using a Kaggle dataset. I changed the dataset a little and want to predict if the ...
-1
votes
0answers
11 views

Polynomial Regression for Matrix

I am new to Python. I have a problem and I hope you can help me with this problem. I have 2 numpy array matrices: $X$ and $Y$. Each matrix has 652 rows and 652 columns. $X^T = X$, $Y^T = Y$. I must ...
2
votes
1answer
57 views

How to merge personalized models together

Let's say I'm building an app like Uber and I want to predict the user's most likely destination based on the user's past history, current latitude-longitude, and current date and time. We have ...
0
votes
1answer
61 views

gradient descent diverges extremely

I have manually created a random data set around some mean value and I have tried to use gradient descent linear regression to predict this simple mean value. I have done exactly like in the manual ...
1
vote
1answer
18 views

Ngram based Langauge Models learned using an Encoder-Decoder Model

I have been going through a Ngram based Langauge Model learned using an Encoder-Decoder Model for Email smart compose. The program output only 1 prediction for given input. I want to know how to ...
0
votes
2answers
118 views
-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
81 views

Need help on Time Series ARIMA Model

I'm working on forecasting daily volumes and have used time series model to check for data stationarity. However, I'm strugging at forecasting data with 90% accuracy. Right now variation is extremely ...
0
votes
1answer
15 views

Predicting a timeseries that includes categorical and numeric data

Given the following properties in a dataset: Type Of Work [T1,T2,T3,...Ti] Measurment Unit [U1,U2,U3,...Ui] Number ...
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
13 views

Low leves of probability observed after modelling.Is it right to scale the probability

I have done modelling on imbalanced class , without any sampling methods. Event rate is around 0.1 ,After modelling I am getting probalities more at the lower side close to zero.I have tried differnt ...
1
vote
1answer
26 views

What's the best way to predict weekly selling data?

I am trying to create a model to predict the units that will be sold for different grocery items say in the next week. I am structuring the problem in a three-step procedure. Group together the ...
0
votes
0answers
15 views

Predicting next failure of car system given previous failures

I have a Dataset of cars including various features just as energy used, power, the model year, rolling law (maximum number of kilometers the car should drive per year) etc. I have also some ...
2
votes
2answers
2k views

Correlation and Naive Bayes

I would like to ask if the Pearson correlation between fields (but not the class field) of a dataset affects somehow the performance of Naive Bayes when applying it to the dataset in order to predict ...
39
votes
5answers
30k views

Should a model be re-trained if new observations are available?

So, I have not been able to find any literature on this subject but it seems like something worth giving a thought: What are the best practices in model training and optimization if new observations ...
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
57 views

Hill Climbing Algorithm - Optimum Step Size

I am implementing a standard hill climbing algorithm to optimise hyper-parameters for a predictive model. The hill climbing algorithm is being applied as part of a two-stage approach: Apply grid ...
1
vote
1answer
56 views

TF Keras Text Processing - Classification Model

I'm trying to put together a script that classifies comments into either adequate or inadequate. I put a question up here earlier with all my code, but I think I've isolated the problem down into the ...
4
votes
1answer
71 views

Predicting change of shapes/coordinates

I'm trying to find a way to predict/calculate how a shape (e.g. outline of a glacier) will change in the future—based on its history (previous shape) and additional factors (e.g. Δtemperature). In my ...
2
votes
1answer
96 views

Store's unseen items sales forecasting

I am working on sales forecasting problem.I am able to provide data about which items got sold and not sold to the algorithm.How to provide algorithm information about items that are not present in ...
3
votes
1answer
43 views

Predicting t+1 from a set of sequences

Say I have have an experiment where I release a single rat into a maze and wait for it to reach the end. Say I also track this rat's position in the maze at various times. Let's do this $n$ times. Now,...
0
votes
1answer
37 views

Prediction: plugin a corelation table (neuron) into a Time-Series Neuron in Keras/ TF

i am adding more details I have a time series of Babies (1,2,3) showing how many problem they have each week (Born week 1 to week 80) and in which organ (14 organ). There is a separate numeric time-...

1
2 3 4 5
18