Question

In: Computer Science

training dataset

training dataset

Solutions

Expert Solution

Answer: As per question I understand that one need to understand what is a training dataset. Training dataset can be explained as:

The training data is basically an initial set of data which helps to understand a program and how to apply the technologies as in neural networks to learn and produce a more polished result. It may be accompanied by the subsequent sets of data called data validation and testing datasets. The other names of training data are training set, training dataset or learning set. The computer understands the machine language hence in order to make computer learn how to process information the training set act as an information material. Computer uses machine learning through algorithms which imitates the abilities of the human brain to take inputs and understand them and produce activations in the brain. The computer gets the artificial neurons to replicate a lot of these processes with the software. Machine learning and neural learning network programs helps to provide a very magnified models to learn hoe a human thought process works. The training data can be structured in many ways by sequential decision trees and algorithm based on the same logic.Any set of raw text or alphanumeric data is present it get manipulated logically also for complicated neural networks which are related to image processing and computer vision the training dataset produce a huge number of images to get in sync with human brains. The basic idea of the training dataset is to make a system logically so strong the it can compete human brain and understand every minute details for this we need the help of the training datasets.


Related Solutions

The following training dataset is “reading email dataset”. This dataset has four features as follows: author,...
The following training dataset is “reading email dataset”. This dataset has four features as follows: author, thread, length, and where to read the mail. According to the features the algorithm has to predict the user’s action whether to read or skip the mail. Use Naïve Bayes classifier to predict the user’s action (skips or reads) when the author of the mail is known, the thread of the mail is follow up, the length of the mail is short, and where...
The following training dataset is “reading email dataset”. This dataset has four features as follows: author,...
The following training dataset is “reading email dataset”. This dataset has four features as follows: author, thread, length, and where to read the mail. According to the features the algorithm has to predict the user’s action whether to read or skip the mail. Use Naïve Bayes classifier to predict the user’s action (skips or reads) when the author of the mail is known, the thread of the mail is follow up, the length of the mail is short, and where...
Which of the following methods can achieve zero training error on any linearly separable dataset? (A)...
Which of the following methods can achieve zero training error on any linearly separable dataset? (A) Support vector machines (B) 3-Nearest Neighbor (C) Linear perceptron (D) Logistic regression Please answer with an explanation for each option on why it may or may not achieve zero training error on any linearly separable dataset.
Describe Hunter's Algorithm for building decision trees. Build a decision out of the following ("training") dataset....
Describe Hunter's Algorithm for building decision trees. Build a decision out of the following ("training") dataset. The goal is to determine if a person is a defaulted borrower given values for the first four attributes. How do you deal with the attribute Annual Income with real values? For a person with values for the first four attributes 11, No, Single, 180K, is this person a defaulted borrower or not according to your newly built decision tree? ID Home Owner              ...
Would you please demonstrate to me how to create dataset A and dataset B, where dataset...
Would you please demonstrate to me how to create dataset A and dataset B, where dataset A has a larger range but smaller standard deviation than dataset B. Then the reverse where data set A has a smaller range and larger standard deviation than data set B.
2. Dataset B consists of the values {10,12,14,24,25,27,28,30,30,32,33,33,34,37,38,38,40,41,43, 44,44,46,47,49,56,58}. (a) What is the median of Dataset...
2. Dataset B consists of the values {10,12,14,24,25,27,28,30,30,32,33,33,34,37,38,38,40,41,43, 44,44,46,47,49,56,58}. (a) What is the median of Dataset B? (b) To one decimal, what is the sample standard deviation of Dataset B? (Don’t calculate this out by hand.) (c) Make a table of the frequency distribution (not the relative frequency distribution) of Dataset B, using the intervals 10 to 19, 20 to 29, 30 to 39, 40 to 49, and 50 to 59. Be sure to appropriately label the table headings. (d)...
To find the dataset needed for this problem, you’ll first need to open the “swiss” dataset...
To find the dataset needed for this problem, you’ll first need to open the “swiss” dataset that is contained in R by running the following line: > data('swiss') Now you can rename the “swiss” dataset and use it to answer the question below. Name the data frame with your UT EID:                         > my_variable <- swiss This dataset contains socio-economic indicators for the French-speaking provinces of Switzerland in the year 1888. Among the variables, “Agriculture” is the percentage of the...
You have three lines of training modules: Company Training (CT), On-line Training (OT), and Academic Training...
You have three lines of training modules: Company Training (CT), On-line Training (OT), and Academic Training (AT). For each sold CT, you will receive $1,000 in revenue, while for each sold OT, you will receive $800 and for each AT, you will receive $700. Each module lasts for one month. To deliver the module CT, UQ-HDTC requires 100 hours of data scientist and computer programmer time. The module OT requires 300 hours of data scientist and 500 hours of computer...
Download the dataset returns.xlsx. This dataset records 83 consecutive monthly returns on the stock of Philip...
Download the dataset returns.xlsx. This dataset records 83 consecutive monthly returns on the stock of Philip Morris (MO) and on Standard & Poor’s 500 stock index, measured in percent. Investors might be interested to know if the return on MO stock is influenced by the movement of the S&P 500 index. Please be aware that return is defined as new price − old price old price × 100%, so it is always reported as a percentage. 6. Fit a linear...
Download the dataset returns.xlsx. This dataset records 83 consecutive monthly returns on the stock of Philip...
Download the dataset returns.xlsx. This dataset records 83 consecutive monthly returns on the stock of Philip Morris (MO) and on Standard & Poor’s 500 stock index, measured in percent. Investors might be interested to know if the return on MO stock is influenced by the movement of the S&P 500 index. Please be aware that return is defined as new price − old price old price × 100%, so it is always reported as a percentage. 1. What is the...
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT