The lazierthanlazygreedy optimizer has been updated to accept two typ…

…es of input for the random subset size:

An epsilon value between 0 and 1
A positive integer

The random subset size is determined as follows:

If epsilon is less than 1:
Random subset size = ((n / budget) * log(1 / epsilon))
Where:

n is the total number of elements
budget is the computational budget
log is the natural logarithm

If epsilon is 1 or greater:
The provided value is directly used as the random subset size

This update allows for more flexible control over the optimizer's behavior, allowing users to specify either a proportion (epsilon) or an exact size for the random subset.

cpp/optimizers/LazierThanLazyGreedyOptimizer.cpp

@@ -195,7 +195,10 @@ std::vector<std::pair<ll, double>> LazierThanLazyGreedyOptimizer::maximize(
     float rem_budget = budget;
     std::unordered_set<ll> remainingSet = f_obj.getEffectiveGroundSet();
     ll n = remainingSet.size();
-    ll randomSetSize = ((double)n / budget) * log(1 / epsilon);
+    ll randomSetSize = static_cast<ll>(epsilon);
+    if (epsilon < 1) {
+        randomSetSize = static_cast<ll>(((double)n / budget) * log(1 / epsilon));
+    }
 
     if (verbose) {
         std::cout << "Epsilon = " << epsilon << "\n";

cpp/optimizers/StochasticGreedyOptimizer.cpp

@@ -31,7 +31,10 @@ std::vector<std::pair<ll, double>> StochasticGreedyOptimizer::maximize(SetFuncti
 	float rem_budget = budget;
 	std::unordered_set<ll> remainingSet = f_obj.getEffectiveGroundSet();
 	ll n = remainingSet.size();
-	ll randomSetSize = ((double)n/budget)* log(1/epsilon);
+	ll randomSetSize = epsilon;
+	if (epsilon < 1) {
+		randomSetSize = static_cast<ll>(((double)n / budget) * log(1 / epsilon));
+	}
 
 	if (verbose) {
 		std::cout << "Epsilon = " << epsilon << "\n";

requirements.txt

@@ -1,6 +1,6 @@
 #this file is needed for doc building by readthedocs.org
 sphinxcontrib-bibtex
 pybind11>=2.6.0
-numpy==1.22.0
+numpy
 scipy
 scikit-learn

setup.py

@@ -93,7 +93,7 @@
     #     "tqdm >= 4.24.0",
     #     "nose"
     # ],
-    install_requires=["numpy==1.22.0", "scipy", "scikit-learn", "numba"],
+    install_requires=["numpy>=1.22.0", "scipy", "scikit-learn", "numba"],
     #setup_requires=['pybind11','pytest-runner'],
     tests_require=['pytest'],
     #extras_require={"test": "pytest"},