I have a data set of 80,000 samples (40k 3 axis accelerometer and 40k Gyro data). I am trying to implement KNN and Random Forest for activity recognition on ESP8266 Node MCU. The limited memory of the MCU is the bottleneck of the process.
Is there any method that can reduce the dataset to, say 5000 records without losing any vital information and without affecting overall accuracy? Dimensionality reduction, as I could understand with my non-mathematical background, is reducing the data by dropping less important columns. However, in my case, I cannot drop any column (only 6 columns are there which are x,y,z values of accelerometer and gyroscope).