This is a machine learning question using python (packages scikit/pandaumpy/..etc if you use one not listed please specify thanks) the method that I need to solve this problem is

K-Nearest-Neighbor

For each dataset, we have the training dataset, training label, and test dataset (no need to split the data it is already done). (We need to calculate the accuracy and test labels (there is an example below) Please use the training dataset and training label to build the classifier and predict the test label. A class label is represented by an integer. For example, in the 1st dataset, there are 4 classes where 1 represents the 1st class, 2 represents the 2nd class, etc. Note that, there exist some missing values in some of the dataset (a missing entry is filled by 1.00000000000000e+99), please fill the missing values before perform your classification algorithm (already done).

Here is the link to the .csv files we only need to use TestData1. TrainData1, and TrainLabel1

I changed the 1.00000000000000e+99 to 999999999 for convienence

http://codd.cs.gsu.edu/~jvaughn13/ML2.html

The goal is to find the accuracy (as high as possible) along with the test labels... here is a small example

i started to work on it but i didnt get far... here is my last working code... it uses a single dataset and splits it and for this problem we dont need to do that

Sample Data Training data 2.1 2.1 2.4 2.42.1 2.6 5.2 Training label Test data 3.1 2.2 1.5 2.5 2.6 Please use the training data and training label to predict the test label. For example, if your prediction for the test sample is 1, 2 That is, the first sample in the test dataset (first row) is predicted as 1 and second as 2. Then please return me the test result of each dataset as an individual files Sample Data Training data 2.1 2.1 2.4 2.42.1 2.6 5.2 Training label Test data 3.1 2.2 1.5 2.5 2.6 Please use the training data and training label to predict the test label. For example, if your prediction for the test sample is 1, 2 That is, the first sample in the test dataset (first row) is predicted as 1 and second as 2. Then please return me the test result of each dataset as an individual files