input_toy.yaml

# ----------------Loading graph parameters-----------------------------
dir_nm: "toy_network" # Options: toy_network, toy_network_old, humap, humap2
sep: " " # Options: " ", "\t"
out_comp_nm: "/results/res" 
split_flag: 0
fact: 0.7
perc_transfer: 0.2
use_full: 1
scale_factor: 1.1  # Number of times negatives should be higher than positives 
mode: non_gen # gen means only feature extraction, non_gen is all
# -------------------Training parameters--------------------------------
feats: 6

model_type: "tpot" # Options: tpot, NN
train_feat_mat: "toy_network/results_train_dat.csv"
test_feat_mat: "toy_network/results_train_dat.csv"
model_name: "SVM" #Options: FF_1hidden, log_reg, SVM, rand_forest, extra_trees
# humap with separted train and test sets - tpot result - extra_trees
 
model_dir: "/results/res"
# --------------------Search parameters ------------------------------
seed_mode: "all_nodes" # Options:all_nodes_known_comp, all_nodes, n_nodes, cliques
num_comp: 40 # 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 search_max_neig    
# No. of neighbors considered params
use_all_neigs: 1
thres_neig: 30 # Maximum number of neighbors sampled for checking
min_thres_neig_sorted: 30 # Threshold above which only a percentage of neigs are considered as per sorted weights
perc: 0.7 # 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: 0.1 # Overlap threshold = 0.7/0.9
infer_overlap_threshold: "y"

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