c++ project -- 8
Paiement à la livraison
Build a binary tree to help detect the type of Breast Cancer tumors.
Benign tumors have not yet spread to other parts of the body whereas Malignant tumors have already spread to other parts of the body. A study has been published that uses a Binary Decision tree to determine if a patient has benign or malignant breast cancer tumors to within a 94.5% accuracy.
We will build that binary decision tree as shown in Figure 13, that runs on a dataset with the information as shown in Table 3.
The data that we would like to run on will be in the csv file format in Figure 12, without the diagnosis (column K in the CSV).
You are to read in the data of patients from file, run the data through the binary decision tree and output the results as shown with the diagnosis Benign or Malignant (Figure 12).
Store the results in a new file named ‘[login to view URL]’ following the same format as the input file, replacing the last column (0) with 2 or 4 based on the result for that row.
After processing all the rows in the file print a summary showing the following:
• Total Patients Processed
• Total Benign
• Total Malignant
• Total Invalid Patient
Nº du projet : #37475015
À propos du projet
11 freelances font une offre moyenne de 25 $ pour ce travail
Hello. I read your requirement i will do that. Please come on chat we will discuss more about this. I will waiting your reply.
Hello, Mohammed! I will perfectly develop a binary tree for detecting the type of Breast Cancer tumors, based on my strong C/C++ Programming and Algorithm experience in a short time. Please open the chat with me so tha Plus
Hello dear! To build a binary tree for the detection of type of breast cancer is the most easiest task which can be done in just few hours. I've a strong grip in handling this type of projects and I can do it perfectly Plus
⭐Dear Client!⭐ I am Algorithm EXPORT. I have rich experience in Python and C/C++. I've read your job description and I am sure I can COMPLETE YOUR TASK with high quality. I am good at algorithms and very familiar wit Plus