Synthetic sampling method for data conditioning of multiclass imbalanced datasets is proposed. Modified particle swarm optimization technique and Hybrid forward feature selection method for multiclass classifier is developed. Effectiveness of these techniques is demonstrated on extremely imbalanced medical datasets