input_yeast_mips.yaml

# ----------------Loading graph parameters-----------------------------
dir_nm: "yeast" # Options: toy_network, toy_network_old, humap, humap2
sep: " " # Options: " ", "\t"
netf_nm: "/dip.txt" 
comf_nm: "/mips.txt" 
comf_test_nm: "/TAP-MS.txt" # Make sure no extra rows are present
comf_nm_all: "/all_complexes_yeast.txt"
out_comp_nm: "/results/res" 
use_full: 0
scale_factor: 1.1  # Number of times negatives should be higher than positives 
split_flag: 0
mode: non_gen # gen means only feature extraction, non_gen is all 
# -------------------Training parameters--------------------------------
feats: 6

classifier_file: "yeast/results_conn_red_mips/res_classifiers.txt"
model_type: "tpot" # Options: tpot, NN
train_feat_mat: "yeast/results_conn_red_mips/res_train_dat.csv"
test_feat_mat: "yeast/results_conn_red_mips/res_test_dat.csv"
model_name: "tpot_select" #Options: FF_1hidden, log_reg, SVM, rand_forest, extra_trees, estimator_SVM
# humap with separted train and test sets - tpot result - extra_trees
# best_classifier: "LogisticRegression" # Only for tpot_select - ExtraTreesClassifier
 
model_dir: "/results_conn_red_mips/res"
# --------------------Search parameters ------------------------------
seed_mode: "all_nodes_known_comp" # Options:all_nodes_known_comp, all_nodes, n_nodes,cliques
num_comp: 10 # Options: 10, 7778, 1500 - only for n_nodes mode

run_mode: "parallel" # Options: serial, parallel
max_size_thres: 50

search_method: "search_top_neigs" # isa, metropolis, search_top_neigs, search_max_neig 
    
# All methods except max_neig    
use_all_neigs: 1
thres_neig: 30 # Maximum number of neighbors sampled for checking 
min_thres_neig_sorted: 100 # Threshold above which only a percentage of neigs are considered as per sorted weights
perc: 0.9 # Percentage of neighbors to check for adding new node
explore_prob: 0.01 # use 0.1 for top_neigs 
# Metropolis algorithm params
prob_metropolis: 0.1

# ISA params
T0: 0.88
alpha: 1.8

over_t: 0.9 # Overlap threshold = 0.7/0.9

# Evaluation parameters
eval_p: 0.5 # threshold in metric for evaluation of complexes