Abstract: An approach is provided for map updates using a machine learning-based persistence filter. The approach involves, for example, processing sensor data collected from vehicles to determine positive observations and/or negative observations of a map or geographic feature. The method also comprises providing the positive and/or observations as an input sequence to a machine learning model. The machine learning model, for instance, includes an input layer that feeds the input sequence to a long short-term memory (LSTM) layer or other type of recurrent neural network (RNN) layer. The LSTM or RNN layer connects to a fully connected layer and then to an output layer. The output layer outputs a predicted sequence of positive and/or negative observations. The method further comprises initiating an update of a geographic database to add, remove, or update the geographic feature based on the predicted sequence.