Questions tagged [data-science-model]

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Key Glossery for Data Science

Please share the basic Keywords used in Data science and description. I am new to Data science and its helpful if i know the Data science keywords with there definitions. Regards, Nigam333
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Microsoft's Professional program for Data Science vs Azure Data Scientist Associate [closed]

Provided that I know nuts and bolts of Data Science. To make use of available leisure time(limited) and for an additional entry on my resume, I would like to know if I should take Microsoft's ...
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Split the dataframe into mutiple rows. [closed]

df = pd.dataFrame({ 'EmployeeId' : ['123','124','125','126','126'], 'City' : ['Nairobi|Mombasa','Nakuru|Nairobi|Kisumu' ,'Nairobi|Mombasa',Nairobi|Nakuru,'Mombasa']})
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to train a NER model Would you make corpus case-sensitive or not? [closed]

to train a NER model Would you make corpus case-sensitive or not?
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1answer
36 views

Machine Learning classification problem

I'm trying to do this classification problem, depicted in the following Figure. The task is to separate the blue elements from the red elements in a cartesian (x,y) coordinate system. I have to: ● ...
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14 views

Is this the case of data leakage?

Let's say, I have the dataframe with numerical features A, B, C. I do not have the target variable but I extract the target variable Y from the features A, B, and C. E.g. ...
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0answers
11 views

Guidance on sequencing the data science professional courses

I am planning to start data science online professional courses at Harvard University, but I don't which course should I begin with . I request for help in sequencing these courses below so that I can ...
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1answer
25 views

what is learning rate in neural network?

When I am creating a model using Keras we should define the learning rate(lr) in that optimizer method Please refer to the below code. ...
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0answers
9 views

KS-Score Methods

I came across 2 methods to calculate KS-Score and select best probability threshold. Decible Method TPR - FPR Is there any specific scenario on which it depends which method to select. or we cna ...
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1answer
21 views

What is neural structure learning in tensorflow?

What is neural structure learning? what is the difference between neural network vs neural structure learning?
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0answers
14 views

What is regularization in machine learning? [closed]

What is regularization in machine learning? Why do we need this in machine learning?
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1answer
44 views

what is Tensorflow Quantum(TFQ)?

Google announced a new open-source library called TensorFlow Quantum(TFQ) so I am curious to know about Tensorflow quantum. what is TensorFlow Quantum? How it is useful with an existing TensorFlow ...
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2answers
34 views

Is there an unsupervised learning algorithm that can cluster data based on more than two dimensions?

I am just beginning to get into data science and have never posted here before, apologies if this question is worded incorrectly! I am curious if there is an unsupervised machine learning algorithm ...
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1answer
25 views

How is the E(X) of a Poisson distribution lambda? [closed]

I was recently learning about the Poisson distribution, and was very perplexed about the E(X) equaling lambda. Like how did lambda even come into the picture here, isn't it a symbol of wavelength? ...
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1answer
99 views

Does ridge regression always reduce coefficients by equal proportions?

Below is an excerpt from the book Introduction to statistical learning in R, (chapter-linear model selection and regularization) "In ridge regression, each least squares coefficient estimate is ...
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0answers
17 views

How do clustering works in Gravitational Emulation Local Search

I've been reading this paper titled Efficient clustering in collaborative filtering recommender system: Hybrid method based on genetic algorithm and gravitational emulation local search algorithm for ...
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0answers
6 views

How to parallel plot the following table showing improvement of classifier for every subject

parallel_coordinates(data,'Subject', colormap='Dark2', linewidth=5, alpha=.8) plt.ylabel('Direction of Preference $\\rightarrow$', fontsize=12) This is giving me ...
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21 views

Bias of an estimator?

What is p(X;0)actually modelling? What's the difference between the two types of theta? What's happening in this equation and did expectation convert into summation ? Source:https://subscription....
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1answer
35 views

How to test/train a model for realtime data with new data points and classes in a ML pipeline

First, For a text classification problem, if I have trained the model on 2 classes and it gives good accuracy. Now, when I use the model in real-time, there is a completely new class from a totally ...
4
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1answer
25 views

Does k fold cross validation become less useful when number of observations is very large?

As seen in the accepted answer for variance of k-fold cross validation , the simulation shows that k-fold CV has the same test error rate for different values of k when n=200. Does this mean that k-...
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0answers
14 views

Why gaussian assumption in GMM-HMM ASR?

I am reading a book titled "Speech and Language Processing" by Daniel Jurafsky and James . For Acoustic vector , I would like to know why Gaussian assumption is made ? I searched over net and could ...
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1answer
39 views

Forecasting with a Machine Learning Algorithm

Im sorry if it is a too general question, but i am stuck somewhere between perfect and adequate in my model. So, i wanted to ask here. If it is not a suitable question, your negative feedbacks are all ...
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0answers
17 views

Comparing PCAP Datasets

I'm having some issues coming up with the best approach to compare two PCAP files. So I have two PCAPs, the first is a known bad application. The second is an unknown application. What I would like ...
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0answers
16 views

A Productive way to archive trained models?

Currently, I am working on my thesis which is built on LSTM networks and I am using PyTorch library. However I am struggling to ...
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0answers
31 views

Generalised Estimating Equation (GEE) vs. Recurrent Neural Network (RNN)

Has anyone looked into or know what is the difference between a GEE model and an RNN model in terms of what these two models are doing? Apart from the differences in structure of these two models ...
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0answers
30 views

K in the Naming of Models and Techniques

Why is k chosen for the names k-nearest neighbors and k-fold cross validation? Is it arbitrary or just another mysterious naming?
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1answer
18 views

Memory efficient encoding logic for group categories

I have a huge dataset with categorical data. It is comprised of alerts having multiple properties. Each alert belongs to a group, and some even belong to multiple groups. It looks somewhat like this: ...
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0answers
19 views

Variable selection involving mixture of numerical, high cardinal,low cardinal features

Consider a dummy dataframe: A B C D …. Z 1 2 as we 2 2 4 qq rr 5 4 5 tz rc 9 This dataframe has 25 independent variables and one target variable ,the ...
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1answer
29 views

How to calculate the final adjusted weights for a neural network model

My understanding of a neural network algorithm is the 1st row/observation of the dataset is inputted into the NN model and then backpropagation happens to adjust the weights, until some condition is ...
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0answers
14 views

Interpreting Adaboost model results

I'm trying to get a better grasp of model interpretability using many different kinds of models for a binary classification problem. Quick note: By interpretability in this case, what I mean is ...
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1answer
34 views

Data augmentation solutions for tabular/structured data

Are there any reliable libraries or methods for tabular/structured data (with numerical and categorical features) augmentation? Could you share some? Basically I believe inventing/augmenting more ...
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1answer
43 views

Determine model hyper-parameter values for grid search

I built machine learning model for Ridge,lasso, elastic net and linear regression, for that I used gridsearch for the parameter tuning, i want to know how give value range for **params Ridge ** below ...
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1answer
18 views

Random Parameters to fix in ML to perform controlled experiments

Many algorithms and methods in modern Machine Learning techniques contain randomness, and because of that, running the same ML script several times can result in different outputs, therefore accuracy ...
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1answer
42 views

Data Science Pipelines vs Common CD/CL

What is the advantage of Data Science Specific CI/CD (kubeflow, Algo, TFX, mlflow, sagemaker pipelines) vs the already baked flavors that are more generic: Jenkins, Bamboo, Airflow, Google Cloud Build,...
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2answers
76 views

Anomaly Detection/Novelty detection

I have a data-set that has over 6 million normal data and around 50 anomaly data.Those anomaly data is identified by manually(monitoring the user`s activity over camera and identify). I need to ...
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1answer
23 views

variables selection in regression models

I develop price prediction data model using multiple linear regression, ridge, lasso and elastic net regression, initially I had 215 variables. after creating models I ran a python code to check how ...
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1answer
30 views

Machine learning analysis for data set

I have a data set that contains houses, different features, and its prices. I'm trying to do an advanced analysis for this data set, I already did house price prediction analysis using different ...
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1answer
22 views

How to build a unbiased predictive ML model when the record of the event is less compared to the total number of records?

I am trying to build a model that will predict the communication loss of a wireless device. For now I am using RandomForestClassifier along with Device and Location as the features. I am getting both ...
2
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1answer
56 views

How to validate regex based Resume parser efficiently

I am using rule based logic to extract features from resume. Basically I am trying to find if the candidate switched the company in less than 1 year. So I have the code in place to find it using ...
2
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1answer
52 views

Feature extraction from resume using Python without rule based logic

I am working on a resume parser project. Currently, I am using rule-based regex to extract features like University, Experience, Large Companies, etc. So basically I have a set of universities' names ...
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0answers
35 views

What is the difference between “fit_transform” and “transform” methods when using “SimpleImputer”? [duplicate]

I have following code, I am not able to understand the difference between use of fit_transform() and transform() method in this ...
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0answers
12 views

Using Kfold on a facial landmarks model

i am currently working with helen dataset to predict facial landmarks. Currently running the program on a Geforce 1070. The highest batch size i can give is 230 and i am getting a loss of 3 and ...
2
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1answer
85 views

Multiclassification Error: NotFittedError: This MultiLabelBinarizer instance is not fitted yet

After picking the model, when I try to use it, I am getting error - "NotFittedError: This MultiLabelBinarizer instance is not fitted yet. Call 'fit' with appropriate arguments before using this ...
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1answer
34 views

what are the steps in adaboosting?

I went through adaboost tutorial and below are my simplified understanding: Sample weight of equal value is given to all sample in dataset. Stumps are created which uses only one feature from data ...
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0answers
21 views

How to calculate precision and recall?

There is a class-imbalanced labeled dataset with 100'000 samples. 90'000 is "0" and 10'000 is "1". There is a model that predicts the labels. It was runned on the class-balanced (10'000 of "0" and 10'...
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3answers
32 views

How does one define the possibility space of valid priors (models)?

When one trains a model on data of any complexity one inevitably ends up with a one particular model among a vast many possible models that would make similar (or even, the same) predictions. For ...
2
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1answer
30 views

Correct interpretation of summary_plot shap graph

While through the various resources online to understand the shap plots, I ended up slightly confused. Find below my interpretation of the overall plot given in examples - Shap value 0 for a feature ...
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1answer
41 views

Differences between normalization and standarization in multiple regression

Consider the following question regarding multiple regression 1) Can someone explain why we have to transform dependent variable using log-transformation (Normalization) when appear positive skewed y ...
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1answer
32 views

how to determine percentage below which a feature can be removed from a model

Let feature $feat$ contain one value $A$ that occurs 5% of the time, while 95% of the time it is empty. Instead of arbitrary saying features that have less than 5% should not be included into the ...

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