The best answer to the question above would be option C: <span>create a bar graph that shows population totals for each nation. Since it emphasizes a visual comparison, the best way to do this is to create a bar graph. So in a bar graph, the numerical values of the variables are also presented such as the population total of each nation. In addition, the rectangular bars can easily show you the difference between each nation which makes this an ideal visual tool for comparison.</span>
Answer
• Maintaining eye contact
• Paying attention in the talk
• Listening without jumping to conclusion
• Formulating a picture in mind as you listen
• Avoid interruption to suggest solutions
• Asking clarification when the speaker has paused
• Asking questions to improve understanding
• Understanding the mood of the speaker
• Giving the appropriate feedback
Explanation
A person can improve his active listening skills by being aware of his or her personal style of communicating. A good listener is productive and able to influence others when talking because he or she will have mastered the technique of persuading and negotiating with audience when talking. The journey to becoming an active listener is through paying attention, showing that you are following the speaker ,providing good feedback, avoiding judging the speaker and providing the appropriate feedback.
Answer:
b
Explanation:
First, we need to initialize the classifier.
Then, we are required to train the classifier.
The next step is to predict the target.
And finally, we need to evaluate the classifier model.
You will find different algorithms for solving the classification problem. Some of them are like decision tree classification etc.
However, you need to know how these classifier works. And its explained before:
You need to initialize the classifier at first.
All kinds of classifiers in the scikit-learn make use of the method fit(x,y) for fitting the model or the training for the given training set in level y.
The predict(x) returns the y which is the predicted label.And this is prediction.
For evaluating the classifier model- the score(x,y) gives back the certain score for a mentioned test data x as well as the test label y.
The programmer solves the problems of a user by expressing an algorithm in a programming language to make a program that can run on a computer.
