Aishwarya Jhadav

What does the DOCKER_HOST variable do?

To solve $docker_host you can go through the below-mentioned solution: In this case, Client is the docker command in OSX Host is basically the boot2docker virtual machine. Daemon is basically a service running in the background inside boot2docker. When you type in the docker commands they work because the terminal…

Devops

Answered Jun 15, 2021 · 1.7K Views Read answer →

selenium - chromedriver executable needs to be in PATH

Incase, you are facing chromedriver' executable needs to be in path error in your code then follow the steps shown below: Add it to your system path Put it in the same directory where you have your python script Specify the location directly via executable_path like this: driver =…

Java

Answered Jun 1, 2021 · 1.2K Views Read answer →

Java project in Eclipse: The type java.lang.Object cannot be resolved. It is indirectly referenced from required .class files

Java

Answered Apr 10, 2021 · 793 Views Read answer →

How might I convert a DateTime object to milliseconds since epoch (Unix time) in Python?

Python

Answered Mar 4, 2021 · 1.1K Views Read answer →

What is git prune?

The git prune command is an inside housekeeping utility that erases lost or "stranded" Git objects. Inaccessible items are those that are unavailable by any refs. Any submit that can't be gotten to through a branch or tag is viewed as inaccessible or not present. git prune is by and large not executed…

Devops

Answered Feb 13, 2021 · 1.1K Views Read answer →

How to perform selection and indexing of data frame elements in R?

To perform such operations, we have to build a dataframe first # Some made up weather data days

Data Science

Answered Jan 2, 2020 · 851 Views Read answer →

When to choose one-hot encoding and word embedding?

One-hot encoding is a method which vectorizes any categorical features. It can be done just by adding one to each category. It is simple and fast but it gives rise to issues like ‘curse of dimensional’ when a new dimension will be added to every category. Word embedding can handle large amount of text data and it…

Data Science

Answered Dec 24, 2019 · 2.8K Views Read answer →

A user is using R to implement kNN classification model. The knn function in'class'package contains a parameter called cl: What does it mean?

KNN or K Nearest Neighbor is a non parametric or lazy learning algorithm which works while testing the data. It memorizes the unseen test data by comparing the observation with nearest training observations which are also time consuming while testing each data point. The accuracy of this algorithm depends on the value…

Data Science

Answered Dec 20, 2019 · 808 Views Read answer →

A user is getting a value error in Logistic Regression .How to solve this? He tried dropping the su

Here the error is due to the different shapes of train and test data of the feature variables. In test data,

Data Science

Answered Nov 30, 2019 · 756 Views Read answer →

Explain with an example how to find out the p-values in order to avoid multicollinearity?

In logistic regression, p-value can be found by the following codeAfter training the data we can find the following p-valuesHere, summary code generates the following output, among which the most insignificant variable is purpose_A

Data Science

Answered Nov 30, 2019 · 840 Views Read answer →

Why is log(odds) considered and not probability in logistic regression?

Logistic regression applies maximum likelihood estimation which transforms the dependent variable into a logitvariable (natural log of the odds of the dependent variable occurring or not) with respect to independent variables. In this way, logistic regression estimates the probability of a certain event occurring. In…

Data Science

Answered Nov 28, 2019 · 1.1K Views Read answer →

A user has a dataset of reviews which has a class label of positive/negative. He is applying Decision Tree to that reviews dataset. How to get the feature importance using the decision tree…

Below is the code X_tr, X_test, y_tr, y_test = cross_validation.train_test_split(sorted_data['Text'], labels, test_size=0.3, random_state=0) # BOW count_vect = CountVectorizer() count_vect.fit(X_tr.values) final_counts = count_vect.transfrom(X_tr.values) # instantiate learning model k = optimal_k # Applying the…

Data Science

Answered Nov 17, 2019 · 715 Views Read answer →