Questions tagged [data-science-model]
The data-science-model tag has no usage guidance.
381
questions
1
vote
0answers
6 views
What are the business metrics I should track to evaluate a recommender model deployed on an e-commerce website?
Can you suggest some google analytics metrics such as (click or impressions etc) to evaluate a recommender model deployed on an e-commerce website.
-1
votes
0answers
6 views
Here is the Case Study for Next Generation Database [closed]
Design an application which will have all operations like create, update, delete, display employees using MongoDB database.
Front-end should be in HTML and CSS backend should be in PHP
Design ...
-1
votes
2answers
33 views
Machine Learning for medical researchers [closed]
My friend is a medical researcher and he want to use machine learning for prediction.
Is there any one who is not a computer science person and he learnt programming and machine learning in a very ...
3
votes
0answers
23 views
What is the difference between trax vs tensorflow?
What is the main difference between trax vs tensorflow?
both of them deep learning library and implemented by google team.
https://github.com/google/trax
https://github.com/tensorflow/tensorflow
1
vote
0answers
27 views
How does stacking help Bias and Variance?
How does stacking help in terms of bias and variance?
I have a hunch that stacking can help reduce bias but i am not sure, could someone refer to a paper?
0
votes
1answer
20 views
What is the difference between cache() vs prefetch() in tensorflow?
I have gone through the TensorFlow documentation.
What is the difference between cache() vs prefetch() in TensorFlow?
When ...
0
votes
0answers
27 views
Confusion Matrix after XGBoost is showing positive as negative class
Please can you help me with confusion matrix. I've implemented the XGBoostClassifier. After fitting the model when I looked to the confusion matrix to view the performance on Test data. The confusion ...
0
votes
1answer
18 views
How to convert input numpy data to tensorflow tf.data to train model in tensorfow?
I am working on an image classification problem using TensorFlow. I have converted my input image dataset and label into NumPy data but it takes more time and more ram to load all the data into memory ...
0
votes
0answers
11 views
Forecasting Weekly Average Usage
In python/pandas what would you suggest as a couple of good basic methodologies to use to forecast weekly average usage of user activity on a given platform?
1
vote
1answer
23 views
train test data split up in datasets
In a dataset consisting of 1,000 samples, it has been shown that a 70-30 split
(i.e. 70% of the samples used for training, 30% for validation) will provide a good estimation
of the test accuracy of ...
0
votes
0answers
10 views
How to correctly lemmatize the text column in R?
I'm working on a project in Natural Language Processing. I have a data frame that has a text column. I have to lemmatize that text column. I'm using lemmatize_strings() function in R. However, there's ...
0
votes
1answer
18 views
Microsoft custom vision vs Tensorflow model?
I am planning to implement my own image classifier model using TensorFlow instead of a custom vision platform.
what is the biggest difference between custom vision(https://www.customvision.ai/) vs ...
-1
votes
0answers
4 views
Bootstrap Using original test set instead of using out of sample for model validation
I'm using German credit classification dataset by UCI repository. I initially split train and test set. And then, I used bootstrapped with replacement from the original dataset instead of training set....
2
votes
1answer
24 views
what is difference between Logistic regression and SGDClassifier with log loss OR SVM and SGDClassifer with hinge loss?
Can we just use SGDClassifier with log loss instead of Logistic regression, would they have similar results ?
2
votes
0answers
19 views
Calculating the lower and upper bounds forVC-dimension of a decision tree
I have a problem finding the lower and upper bounds of the decision tree. Suppose there is a decision tree with a hypothesis space of depth 2 and an input space with 10 variables (the variables take ...
1
vote
1answer
31 views
Is there a standardized way to do data analysis?
Is there a standard way to do data analysis?
So for example, something like this:
1. Data mining
2. Data cleaning
3. xx
4. Data and result interpretations
I ...
-2
votes
0answers
12 views
isnull(). returning incorrect figure [duplicate]
In the below code, I am trying to bind the prediction result in new dataframe. However, in new dataframe it is showing incorrect values.
I do not know why ...
0
votes
0answers
30 views
isnull().sum() returning incorrect figure
I am doing a prediction using RandomForestRegressor.
Below is the code for test data:
...
0
votes
0answers
14 views
Multiple input single output supervised learning ANN problem
I have a dataset of 120 tuples giving a singular output. I want to implement ANN in estimating the input which is affecting the output most. A case of optimising the input to maximise the output.
ANN ...
0
votes
1answer
27 views
Context Based Embeddings vs character based embeddings vs word based embeddings
I am working on a problem that uses English alphabets in the text but the language is not English. Its a mixture of English and different language text. But all words are written using English ...
1
vote
0answers
9 views
Parameter estimation using convolutional for exponential functions
I was inspired by this paper where the authors fed an 1-dimenisonal input waveform to the simple convolutional neural network and got an estimate of four parameters of the analytic model. This ...
0
votes
0answers
11 views
Linear Regression Model Validation with Transformed Data
I worked on a model that I applied a log10 transformation to the dependent variable. I am having trouble with manually calculating the R2 for both train and test dataset. The model looks like this.
<...
-1
votes
1answer
32 views
What's the right input for gpt-2 in NLP
I'm fine-tuning pre-trained gpt-2 for text summarization. The dataset contains 'text' and 'reference summary'. So my question is how to add special tokens to get the right input format. Currently I'm ...
1
vote
0answers
14 views
Rank advertisement and Score keywords used in advertisement based on its performance
I am trying to classify my advertisements and trying to understand which advertisement is performing better than others and why.
Step - 1: compare two ads based on CTR.
The problem here is I am ...
1
vote
1answer
44 views
Model retraining
I have trained my model with RandomForestRegressor, but now my training data is updated continuously. So I have to train my model with all the train data set i.e past and new data, or can I directly ...
2
votes
2answers
39 views
What to do when seed has a big impact on model performance?
I have a training procedure set up for an image recognition task. Each time I train a model, I record training loss, validation loss, validation precision and validation recall.
Recently I switched ...
0
votes
0answers
112 views
UserWarning: No contour levels were found within the data range
I am running the exact example give in this SVM example of Scikit learn without any modification.
I get the following warning.
...
1
vote
1answer
22 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
2
votes
1answer
81 views
Why does the smallest LSTM I can make perform so well on this time series forecast?
So I've been playing with some different forecasting methods on a data set that I have done some more basic analyses for in the past. Without going into to much detail, it's population data over time ...
0
votes
1answer
19 views
Twitter Data-Analyse: What can I do with the data?
I retrieve data to a specific topic from Twitter and did my sentiment analysis on it. I never did anything in NLP, etc. So what else can I do with that? "Main goal" would be to find out if ...
1
vote
1answer
35 views
How to normalize technical skills of IT using machine learning?
I have a huge collection of skills collected/scraped from various online sources. It was huge effort done by our team.
Now, the biggest challenge we are facing is trying to normalize the skills back ...
0
votes
1answer
17 views
How to increase sales and revenue of a Client?
I was asked this in an interview for a Data Scientist position:
Lets say Holland and Barret came to you and said they'd like to increase their sales and revenue. How will you go about it?
My answer ...
1
vote
0answers
13 views
Marketing Channel Recommender System [closed]
This dataset is collected by a drug making company trying to sell its drug to doctors of different specializations.
The drug company has made promotional activity for its brand
The promotional ...
0
votes
0answers
35 views
Hypothesis Testing - Median Test for linear regression model given standard error and co-efficient
I need help approaching this particular problem on hypothesis testing.
A researcher believes that a diet high in raw cornstarch would increase the median blood glucose levels by 20. The diet can ...
0
votes
1answer
19 views
finding similarity of a new datapoint
I have built a recommendation engine using cosine similarity. When I want to find all the records similar to a given record that is already present in the dataset it works. Consider a case, a user ...
1
vote
1answer
47 views
Public dataset for news articles with their associated categories for multilabel data classification
I am wondering if there are any public datasets of news, like New York Times (NYT) or similar to various news categories such as politics, entertainment, lifestyle, general news, sports etc.
I want to ...
0
votes
2answers
28 views
What is the value of AIC criterion if RSS is 0? [closed]
The AIC formula is :
$AIC = 2k + n Log(RSS/n)$
So if RSS is equal to 0, it is undefined. How do I deal with this? What value should it take?
4
votes
2answers
55 views
Sklearn: applying cost complexity pruning along with pipeline
I have a data set with categorical variables. I have defined a decision tree algorithm and transformed these columns to numerical equivalent using one hot encoding functionality in sklearn:
Create ...
0
votes
0answers
91 views
Variational Autoencoder with custom loss in Keras giving “nan” loss while training
I am trying to write a simple Variational Autoencoder for a numerical dataset as opposed to images such as MNIST etc. I am basically replicating the keras blog post on this subject (with obvious ...
0
votes
1answer
39 views
Understanding Confidence Interval
I am trying to understand the concept of Confidence Intervals. What is the meaning of point estimates and confidence intervals? What I understood is the point estimate in confidence interval is ...
1
vote
0answers
27 views
How can I make a better unsupervised text classifier model? Is POS tagging part of Machine Learning and Data science?
I have got complaints data, which is not good, and often contains less than 3 words in every complaint (sometimes so short that only one word of them makes sense). The objective is to find what's ...
2
votes
0answers
27 views
How to improve model performace when model shows a systemic pattern in residues
I'm working on a regression model using Boosting algorithms (CatBoost, XGBoost, and LightGBM). All models give similar accuracy of 0.2 RMSE (Target varies from 0 to 1). I obtained the following plots ...
1
vote
0answers
11 views
Are there different types of confidence values?
Query related to apriori association in ML. I am learning apriori association from a teacher. I have a simple dataset of five transactions as follows.
T1: {Milk, bread}
T2: {Milk, bread}
T3: {Milk, ...
0
votes
0answers
29 views
What algorithmic solution would you use for this scenario?
The Project In a Nutshell
Use an algorithmic solution to predict with 70%+ accuracy in as close to real-time as possible the increase and decrease of at least three numeric incremental movements for a ...
-2
votes
1answer
62 views
Which machine learning model to choose? [closed]
I am a beginner in data science. I am facing the problem of choosing the most appropriate algorithm for my specific problem. I am building a recommendation system that gives students insight into ...
0
votes
1answer
33 views
How can a ML algorithm learn to classify fake news? [duplicate]
I am new in Machine learning techniques and in fake news detection by using these algorithms (SVM, nn, logistic regression,..).
I would like to understand how an algorithm can learn from a training ...
1
vote
1answer
19 views
How to handle fixed values for variables in pre-processing
I have a dataset which contains few variables whose values do not change. Some of the variables are non-numeric (for example all values for that variable contain the value 5) and few variables are ...
1
vote
1answer
36 views
How to apply multiple filter in Data Frame? [closed]
How to implement multiple filters for checking data cell in a range ?
Suppose, I have a list of numbers like,
...
1
vote
2answers
41 views
What is the purpose of the 'train model' step in data mining?
My understanding is that training a model is something done in machine learning using training data so that the model can predict values when new data is given to it.
Data mining is the process to ...
2
votes
1answer
21 views
How do I deploy a model when using Stratified K fold?
I have used Stratified K fold for learning the model . Below is the python code:
...
