How to do incremental training using 2 batches of dataset, where the tool is anything except neural network

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I am a novice in this field. I have two training datasets. 1st I want to train the machine with Dataset T1 (from fisherirish) which has 50 entries, After that I want to train the already trained model with a new dataset T2 , which has also 50 entries. My testing dataset is Test(with 50 entries) and then I want to see the classification accuracy.
Using tree what i did was
load T1 %50 entry
X = meas;
Y = species;
Mdl = fitctree(X,Y)
label = predict(Mdl,Test)
Please help me how to proceed to find the accuracy for the first level training. Then how to use this Mdl to train again using T2 and again predict using Test

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